diff --git a/examples/demo_autotm.ipynb b/examples/demo_autotm.ipynb new file mode 100644 index 0000000..b0dd0d0 --- /dev/null +++ b/examples/demo_autotm.ipynb @@ -0,0 +1,3351 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "fbf190e5-3040-452b-bc63-e0cafe2a711f", + "metadata": {}, + "source": [ + "# Topic modeling with AutoTM" + ] + }, + { + "cell_type": "markdown", + "id": "5e5bc8d9-83c8-4194-a9cb-cd89636572ae", + "metadata": {}, + "source": [ + "Topic Modeling is a powerful technique that unveils the hidden structure of textual corpora, transforming them into intuitive topics and their representations within texts. This approach significantly enhances the interpretability of complex datasets, making it a breeze to extract meaningful insights and comprehend vast amounts of information." + ] + }, + { + "cell_type": "markdown", + "id": "b0238f02-ded3-4945-b1ec-4cfb72d5f9b6", + "metadata": {}, + "source": [ + "In this tutorial we will train topic modeling on the set of imdb reviews to understand the main topics." + ] + }, + { + "cell_type": "markdown", + "id": "b4947fbb-3b3e-418c-a4eb-b0288d1d807e", + "metadata": {}, + "source": [ + "### Installation" + ] + }, + { + "cell_type": "markdown", + "id": "0ca1c7ec-5da5-44b4-b033-aaf05cac2e0f", + "metadata": {}, + "source": [ + "Pip version is currently available only for linux system. You should also download ```en_core_web_sm``` from ```spacy``` for correct dataset preprocessing. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9e6ba89e-c8b6-48c0-9fed-5e69882055df", + "metadata": {}, + "outputs": [], + "source": [ + "! pip install autotm\n", + "! python -m spacy download en_core_web_sm" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "2c9053b4-d848-46b9-9026-199e9b52f405", + "metadata": {}, + "outputs": [], + "source": [ + "from autotm.base import AutoTM\n", + "import pandas as pd\n", + "import logging" + ] + }, + { + "cell_type": "markdown", + "id": "aca59e21-1cac-4086-a03e-af170027b637", + "metadata": {}, + "source": [ + "Now let's load nesessary for English datasets nltk package" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "96f35d96-ca16-4399-90ce-28e547015d6f", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[nltk_data] Downloading package averaged_perceptron_tagger to\n", + "[nltk_data] /root/nltk_data...\n", + "[nltk_data] Package averaged_perceptron_tagger is already up-to-\n", + "[nltk_data] date!\n" + ] + }, + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import nltk \n", + "nltk.download('averaged_perceptron_tagger')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "8b4916f3-31d7-4cda-944f-3bfcbeae7b7b", + "metadata": {}, + "outputs": [], + "source": [ + "logging.basicConfig(\n", + " format=\"%(asctime)s - %(name)s - %(levelname)s - %(message)s\",\n", + " level=logging.INFO, datefmt='%Y-%m-%d %H:%M:%S'\n", + ")\n", + "logger = logging.getLogger()" + ] + }, + { + "cell_type": "markdown", + "id": "5eb34b00-be20-4338-aa53-391603b10cac", + "metadata": {}, + "source": [ + "### Dataset" + ] + }, + { + "cell_type": "markdown", + "id": "6d866e2d-3524-4423-b746-b569e766124f", + "metadata": {}, + "source": [ + "First of all let's download the dataset from Huggingface Datasets. If you do not have the Datasets library you should first install it with ```pip install --quiet datasets``` or you can load your own ```csv``` dataset. " + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "aa8663e5-fae9-44e4-bc92-d146ed0e8774", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Repo card metadata block was not found. Setting CardData to empty.\n", + "2024-06-09 23:40:49 - huggingface_hub.repocard - WARNING - Repo card metadata block was not found. Setting CardData to empty.\n" + ] + } + ], + "source": [ + "from datasets import load_dataset\n", + "\n", + "dataset = load_dataset(\"SetFit/20_newsgroups\")\n", + "pd_dataset = dataset['train'].to_pandas()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a522277c-0c11-4504-a4ab-1719b2456ff3", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "pd_dataset.shape" + ] + }, + { + "cell_type": "markdown", + "id": "02535255-8ead-4a13-8388-c712cc7e9b83", + "metadata": {}, + "source": [ + "In 20 Newsgroups dataset text is in \"text\" column and we will use it s a modeling target " + ] + }, + { + "cell_type": "markdown", + "id": "8a72f311-816b-4fa4-88b5-0785a6f3bf93", + "metadata": {}, + "source": [ + "In AutoTM we have have the basic object ```AutoTM``` that can be used with default parameters or configured for your specific dataset.\n", + "- Basically user should set ```topic_count``` - the number of topics that should be obtained; column name that contain text to process ```texts_column_name``` and ```working_dir_path``` to store the results\n", + "- AutoTm implements dataset preprocessing procedure, so user only needs to define language (special preprocessing is implemented for 'en' and 'ru')\n", + "- User can also manipulate with ```alg_params``` and change algorithms from genetic to bayesian or select another way of quality calculation" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "ebbc7f46-7b1a-4d3b-bc2b-00e943adc3c6", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "autotm = AutoTM(\n", + " topic_count=25,\n", + " texts_column_name='text',\n", + " preprocessing_params={\n", + " \"lang\": \"en\", # available languages with special preprocessing options: \"ru\" and \"en\", if you have dataset in another language do not set this parameter\n", + " },\n", + " working_dir_path='tmp',\n", + " alg_params={\n", + " \"num_iterations\": 50, # setting iteration number to 30 or you can use default parameter\n", + " \"use_pipeline\": True, # the latest default version of GA-based algorithm (default version), set it to False if you want to use the previous version\n", + " # \"individual_type\": \"llm\", # if you want to use llm as a quality measure \n", + " # \"surrogate_name\": \"random-forest-regressor\" # enable surrogate modeling to speed up computation\n", + " },\n", + " )" + ] + }, + { + "cell_type": "markdown", + "id": "3b6734e5-5afd-420b-924b-6b6879c80c40", + "metadata": {}, + "source": [ + "If you worked with ```sklearn``` library than in ```AutoTM``` you should also be comfortable with ```fit```, ```predict``` and their combined version ```fit_predict```. As a reault of ```fit``` you will get a fitted ```autotm``` model that is tuned to your data." + ] + }, + { + "cell_type": "markdown", + "id": "6176c9d6-6e0d-4556-b60e-73332e41e5cf", + "metadata": {}, + "source": [ + "Let's process the dataset" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cc718672-14a8-4292-b7b3-9845d8a168fb", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-06-09 23:43:20 - autotm.base - INFO - Stage 0: Create working dir tmp if not exists\n", + "2024-06-09 23:43:20 - autotm.base - INFO - Stage 1: Dataset preparation\n", + "/notebooks/autotm-env/lib/python3.10/site-packages/numpy/core/fromnumeric.py:59: FutureWarning: 'DataFrame.swapaxes' is deprecated and will be removed in a future version. Please use 'DataFrame.transpose' instead.\n", + " return bound(*args, **kwds)\n", + "2024-06-09 23:43:31 - autotm.preprocessing.text_preprocessing - INFO - Saved to tmp/01cefc7c-1438-4248-8789-9aeb6997bba7/dataset_processed.csv\n", + "2024-06-09 23:43:31 - autotm.preprocessing.dictionaries_preparation - INFO - batches tmp/01cefc7c-1438-4248-8789-9aeb6997bba7/batches \n", + " vocabulary tmp/01cefc7c-1438-4248-8789-9aeb6997bba7/test_set_data_voc.txt \n", + " are ready\n", + "E0609 23:43:31.881521 52299 dictionary_operations.cc:381] Error at line 1, file tmp/01cefc7c-1438-4248-8789-9aeb6997bba7/test_set_data_voc.txt. Expected format: [], dictionary will be gathered in random token order\n", + "2024-06-09 23:43:32 - autotm.preprocessing.cooc - INFO - Calculating cooc: 10 batches were found in tmp/01cefc7c-1438-4248-8789-9aeb6997bba7/batches, start processing\n", + "2024-06-09 23:43:35 - autotm.preprocessing.cooc - INFO - Finished cooc dict collection, elapsed time: 3.4238028526306152, size: 0.062824168 Gb\n", + "2024-06-09 23:43:37 - autotm.preprocessing.dictionaries_preparation - INFO - tmp/01cefc7c-1438-4248-8789-9aeb6997bba7/cooc_df.txt is ready!\n", + "2024-06-09 23:43:38 - autotm.preprocessing.dictionaries_preparation - INFO - tmp/01cefc7c-1438-4248-8789-9aeb6997bba7/cooc_tf.txt is ready!\n", + "2024-06-09 23:43:38 - autotm.preprocessing.dictionaries_preparation - INFO - Calculating pPMI...\n", + "2024-06-09 23:43:40 - autotm.preprocessing.dictionaries_preparation - INFO - Calculating pPMI...\n", + "2024-06-09 23:43:41 - autotm.preprocessing.dictionaries_preparation - INFO - tmp/01cefc7c-1438-4248-8789-9aeb6997bba7/ppmi_tf.txt is ready!\n", + "2024-06-09 23:43:41 - autotm.preprocessing.dictionaries_preparation - INFO - tmp/01cefc7c-1438-4248-8789-9aeb6997bba7/ppmi_df.txt is ready!\n", + "E0609 23:43:41.796114 52299 dictionary_operations.cc:452] Error at line 1, file tmp/01cefc7c-1438-4248-8789-9aeb6997bba7/ppmi_tf.txt. Number of values in all lines should be equal to 3, dictionary will be gathered without cooc info\n", + "2024-06-09 23:43:43 - autotm.base - INFO - Stage 2: Tuning the topic model\n", + "2024-06-09 23:43:43,877 - GA_algo - INFO - Starting experiment: 1717965823\n", + "2024-06-09 23:43:43,878 - GA_algo - INFO - ALGORITHM PARAMS number of individuals 11; number of fitness evals unlimited; number of early stopping iterations 500; crossover prob None\n", + "2024-06-09 23:43:43,883 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:43:43,884 - root - INFO - Doing fitness calculating with individual {\"id\":\"14f834b5-aa39-4237-b4d4-8b3106219dc0\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[19,50313.67078879694,16532.243853954322]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.3833948468508369,0.5411522054698827,0.7779445107555456]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:43:43,885 - root - INFO - Loading dataset entities\n", + "2024-06-09 23:43:43,887 - root - INFO - Reading dictionary from tmp/01cefc7c-1438-4248-8789-9aeb6997bba7/dictionary.txt\n", + "2024-06-09 23:43:44,363 - root - INFO - Dataset entities initialization took 0.48\n", + "2024-06-09 23:43:44,364 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:43:45,630 - root - INFO - Training is complete\n", + "2024-06-09 23:43:45,822 - root - INFO - Wow! all topics\n", + "2024-06-09 23:43:45,823 - root - INFO - Building dictionary\n", + "2024-06-09 23:43:46,012 - root - INFO - COMPONENTS 3.334687021670281 1.208994559296221\n", + "2024-06-09 23:43:46,306 - root - INFO - Fitness estimation took 2.42\n", + "2024-06-09 23:43:46,609 - root - INFO - Deleting bigartm logs: ['bigartm.a.dgx.invalid-user.log.WARNING.20240609-234331.52299', 'bigartm.a.dgx.invalid-user.log.ERROR.20240609-234331.52299', 'bigartm.ERROR', 'bigartm.a.dgx.invalid-user.log.INFO.20240609-234331.52299', 'bigartm.INFO', 'bigartm.WARNING']\n", + "2024-06-09 23:43:46,620 - root - INFO - Doing fitness calculating with individual {\"id\":\"3466b931-8371-4307-b85d-690d0b62d366\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[2,74263.1260807448,79878.16581320445]},{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[25,2124.7887473635374,17346.569432793203]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.09783541293913856,0.540789538959594,0.6134674566968805]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:43:46,621 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:43:48,358 - root - INFO - Training is complete\n", + "2024-06-09 23:43:48,598 - root - INFO - Wow! all topics\n", + "2024-06-09 23:43:48,599 - root - INFO - Building dictionary\n", + "2024-06-09 23:43:48,857 - root - INFO - COMPONENTS 3.4640378397994436 1.7266391782126715\n", + "2024-06-09 23:43:49,212 - root - INFO - Fitness estimation took 2.59\n", + "2024-06-09 23:43:49,535 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:43:49,536 - root - INFO - Doing fitness calculating with individual {\"id\":\"297c805b-088b-49a7-87d5-0a6de572640e\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[16,28306.322419768014,24459.67703105131]},{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[21,45829.36234007214,97615.94599645167]},{\"stage_type\":{\"name\":\"SmoothThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SmoothPhi\",\"distribution\":{\"low\":0.0,\"high\":100.0}},{\"name\":\"SmoothTheta\",\"distribution\":{\"low\":0.0,\"high\":100.0}}]},\"values\":[22,21.020877459080268,52.185056618541694]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.4320638940882422,0.6983689680006248,0.14492820643337656]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:43:49,537 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:43:53,385 - root - INFO - Training is complete\n", + "2024-06-09 23:43:53,877 - root - INFO - Wow! all topics\n", + "2024-06-09 23:43:53,878 - root - INFO - Building dictionary\n", + "2024-06-09 23:43:54,410 - root - INFO - COMPONENTS 3.1519758672580487 0.9776975214413545\n", + "2024-06-09 23:43:55,016 - root - INFO - Fitness estimation took 5.48\n", + "2024-06-09 23:43:55,458 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:43:55,459 - root - INFO - Doing fitness calculating with individual {\"id\":\"af4cfcf5-9653-4a85-883d-a60562867d68\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SmoothThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SmoothPhi\",\"distribution\":{\"low\":0.0,\"high\":100.0}},{\"name\":\"SmoothTheta\",\"distribution\":{\"low\":0.0,\"high\":100.0}}]},\"values\":[12,97.77257171442419,66.68384688592238]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,24.721107846117775,-193.5710957676]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.8163503528704029,0.8873801020019644,0.4035373143094515]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:43:55,460 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:43:56,933 - root - INFO - Training is complete\n", + "2024-06-09 23:43:57,128 - root - INFO - Building dictionary\n", + "2024-06-09 23:43:57,322 - root - INFO - COMPONENTS 1.5035967213444348 0.0\n", + "2024-06-09 23:43:57,515 - root - INFO - Fitness estimation took 2.05\n", + "2024-06-09 23:43:57,779 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:43:57,781 - root - INFO - Doing fitness calculating with individual {\"id\":\"ace65ec7-eb93-42fb-ad52-47b6b9488604\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[30,922.8651352529662,-58.61765505286655]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[27,-459.1118336821203,807.2130291495512]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.25846351499899267]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:43:57,782 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:44:01,038 - root - INFO - Training is complete\n", + "2024-06-09 23:44:01,505 - root - INFO - Wow! all topics\n", + "2024-06-09 23:44:01,506 - root - INFO - Building dictionary\n", + "2024-06-09 23:44:01,962 - root - INFO - COMPONENTS 6.118217103395129 5.345760389906474\n", + "2024-06-09 23:44:02,507 - root - INFO - Fitness estimation took 4.72\n", + "2024-06-09 23:44:02,923 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:44:02,924 - root - INFO - Doing fitness calculating with individual {\"id\":\"0adfb82d-5e7b-42a6-9245-c0fa52167bb7\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[24,93536.13282614859,15161.50047514564]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[27,-465.63938098423273,395.89126481683525]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.4497499961826149,0.11207492014222842,0.7775349387076155]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:44:02,925 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:44:05,994 - root - INFO - Training is complete\n", + "2024-06-09 23:44:06,252 - root - INFO - Building dictionary\n", + "2024-06-09 23:44:06,528 - root - INFO - COMPONENTS 0.46061156563019356 0.0\n", + "2024-06-09 23:44:06,758 - root - INFO - Fitness estimation took 3.83\n", + "2024-06-09 23:44:07,080 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:44:07,081 - root - INFO - Doing fitness calculating with individual {\"id\":\"3fcb830b-3133-416d-b299-303ea45078c8\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[22,-34.375016823222836,115.26143335105144]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:44:07,082 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:44:11,147 - root - INFO - Training is complete\n", + "2024-06-09 23:44:11,770 - root - INFO - Wow! all topics\n", + "2024-06-09 23:44:11,771 - root - INFO - Building dictionary\n", + "2024-06-09 23:44:12,373 - root - INFO - COMPONENTS 6.04010607592878 5.440896700285236\n", + "2024-06-09 23:44:13,074 - root - INFO - Fitness estimation took 5.99\n", + "2024-06-09 23:44:13,541 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:44:13,542 - root - INFO - Doing fitness calculating with individual {\"id\":\"d26cfabc-6cc6-4335-b4aa-d2a127f56a45\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[5,747.8930389408683,766.7776636941433]},{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[27,70478.07499700676,85491.70314354691]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[19,-351.96733800853644,-500.9700674033861]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.22454255072543772,0.41073732308251054,0.5402265081116119]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:44:13,543 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:44:16,243 - root - INFO - Training is complete\n", + "2024-06-09 23:44:16,426 - root - INFO - Building dictionary\n", + "2024-06-09 23:44:16,552 - root - INFO - COMPONENTS 0.0 0\n", + "2024-06-09 23:44:16,666 - root - INFO - Fitness estimation took 3.12\n", + "2024-06-09 23:44:16,864 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:44:16,866 - root - INFO - Doing fitness calculating with individual {\"id\":\"4d51400a-b0e6-4b4c-8ad4-41160f749fb2\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SmoothThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SmoothPhi\",\"distribution\":{\"low\":0.0,\"high\":100.0}},{\"name\":\"SmoothTheta\",\"distribution\":{\"low\":0.0,\"high\":100.0}}]},\"values\":[19,39.018746130681755,59.334612636387405]},{\"stage_type\":{\"name\":\"SmoothThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SmoothPhi\",\"distribution\":{\"low\":0.0,\"high\":100.0}},{\"name\":\"SmoothTheta\",\"distribution\":{\"low\":0.0,\"high\":100.0}}]},\"values\":[29,51.8991196840063,74.20866170982016]},{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[8,28923.435532058327,78406.3604972802]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[5,0.4516736916170343,0.6149157124782801,0.09366914684869043]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:44:16,866 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:44:20,150 - root - INFO - Training is complete\n", + "2024-06-09 23:44:20,607 - root - INFO - Wow! all topics\n", + "2024-06-09 23:44:20,608 - root - INFO - Building dictionary\n", + "2024-06-09 23:44:21,125 - root - INFO - COMPONENTS 2.274690021161785 0.00843633792486774\n", + "2024-06-09 23:44:21,655 - root - INFO - Fitness estimation took 4.79\n", + "2024-06-09 23:44:22,069 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:44:22,071 - root - INFO - Doing fitness calculating with individual {\"id\":\"2b378a82-0dfb-4180-bdb7-a299315b8e37\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[9,12196.549501486432,43649.390246445604]},{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[29,13903.182802145775,81046.9666409797]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[11,-240.53586906391695,182.81867960257932]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.019306010651074845,0.432779596112597,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:44:22,071 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:44:25,151 - root - INFO - Training is complete\n", + "2024-06-09 23:44:25,520 - root - INFO - Building dictionary\n", + "2024-06-09 23:44:25,934 - root - INFO - COMPONENTS 3.967853081542523 0.0\n", + "2024-06-09 23:44:26,388 - root - INFO - Fitness estimation took 4.32\n", + "2024-06-09 23:44:26,752 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:44:26,754 - root - INFO - Doing fitness calculating with individual {\"id\":\"17775cf9-0614-48df-970b-e6e3918e9870\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SmoothThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SmoothPhi\",\"distribution\":{\"low\":0.0,\"high\":100.0}},{\"name\":\"SmoothTheta\",\"distribution\":{\"low\":0.0,\"high\":100.0}}]},\"values\":[3,72.83059407449582,10.973736616243212]},{\"stage_type\":{\"name\":\"SmoothThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SmoothPhi\",\"distribution\":{\"low\":0.0,\"high\":100.0}},{\"name\":\"SmoothTheta\",\"distribution\":{\"low\":0.0,\"high\":100.0}}]},\"values\":[14,63.64481080932214,82.41699206987002]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.11594366356714769,0.7162910207031723,0.5403193180252248]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:44:26,754 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:44:27,673 - root - INFO - Training is complete\n", + "2024-06-09 23:44:27,837 - root - INFO - Wow! all topics\n", + "2024-06-09 23:44:27,838 - root - INFO - Building dictionary\n", + "2024-06-09 23:44:28,005 - root - INFO - COMPONENTS 4.92006388523909 2.5243261967877997\n", + "2024-06-09 23:44:28,281 - root - INFO - Fitness estimation took 1.53\n", + "2024-06-09 23:44:28,569 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:44:28,570 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:44:28,570 - GA_algo - INFO - POPULATION IS CREATED\n", + "2024-06-09 23:44:28,571 - GA_algo - INFO - ENTERING GENERATION 0\n", + "2024-06-09 23:44:28,572 - GA_algo - INFO - PAIRS ARE CREATED\n", + "2024-06-09 23:44:28,588 - GA_algo - WARNING - Cannot perform action after 5 retries\n", + "2024-06-09 23:44:28,591 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:44:28,592 - root - INFO - Doing fitness calculating with individual {\"id\":\"df6e8295-c417-473f-8016-ea090be13ab2\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.5411522054698827,0.25846351499899267]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:44:28,593 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:44:29,109 - root - INFO - Training is complete\n", + "2024-06-09 23:44:29,246 - root - INFO - Wow! all topics\n", + "2024-06-09 23:44:29,247 - root - INFO - Building dictionary\n", + "2024-06-09 23:44:29,341 - root - INFO - COMPONENTS 6.1777531320435655 5.82923675666261\n", + "2024-06-09 23:44:29,547 - root - INFO - Fitness estimation took 0.95\n", + "2024-06-09 23:44:29,825 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:44:29,826 - root - INFO - Doing fitness calculating with individual {\"id\":\"3c5f5647-7e09-49cc-9372-d9ff92e7c5f1\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[19,50313.67078879694,16532.243853954322]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[30,922.8651352529662,-58.61765505286655]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[27,-459.1118336821203,807.2130291495512]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.3833948468508369,0.6935414883927496,0.7779445107555456]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:44:29,827 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:44:34,608 - root - INFO - Training is complete\n", + "2024-06-09 23:44:35,162 - root - INFO - Wow! all topics\n", + "2024-06-09 23:44:35,163 - root - INFO - Building dictionary\n", + "2024-06-09 23:44:35,834 - root - INFO - COMPONENTS 3.0864913135085987 1.6891686217683892\n", + "2024-06-09 23:44:36,487 - root - INFO - Fitness estimation took 6.66\n", + "2024-06-09 23:44:36,999 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:44:37,000 - root - INFO - Doing fitness calculating with individual {\"id\":\"3f491885-6dfa-4ea7-8e63-c02a72cd05d5\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SmoothThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SmoothPhi\",\"distribution\":{\"low\":0.0,\"high\":100.0}},{\"name\":\"SmoothTheta\",\"distribution\":{\"low\":0.0,\"high\":100.0}}]},\"values\":[19,39.018746130681755,59.334612636387405]},{\"stage_type\":{\"name\":\"SmoothThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SmoothPhi\",\"distribution\":{\"low\":0.0,\"high\":100.0}},{\"name\":\"SmoothTheta\",\"distribution\":{\"low\":0.0,\"high\":100.0}}]},\"values\":[29,51.8991196840063,74.20866170982016]},{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[8,28923.435532058327,78406.3604972802]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.09366914684869043]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:44:37,001 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:44:43,087 - root - INFO - Training is complete\n", + "2024-06-09 23:44:43,941 - root - INFO - Wow! all topics\n", + "2024-06-09 23:44:43,942 - root - INFO - Building dictionary\n", + "2024-06-09 23:44:44,776 - root - INFO - COMPONENTS 4.6066883117497515 4.130008016729622\n", + "2024-06-09 23:44:45,738 - root - INFO - Fitness estimation took 8.74\n", + "2024-06-09 23:44:46,266 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:44:46,267 - root - INFO - Doing fitness calculating with individual {\"id\":\"be3b9bd7-11ed-48ce-bbf3-0e0634b19964\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[22,-34.375016823222836,115.26143335105144]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[5,0.4516736916170343,0.6149157124782801,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:44:46,268 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:44:47,467 - root - INFO - Training is complete\n", + "2024-06-09 23:44:47,692 - root - INFO - Wow! all topics\n", + "2024-06-09 23:44:47,693 - root - INFO - Building dictionary\n", + "2024-06-09 23:44:47,899 - root - INFO - COMPONENTS 6.142149864594346 5.705240948959821\n", + "2024-06-09 23:44:48,204 - root - INFO - Fitness estimation took 1.94\n", + "2024-06-09 23:44:48,545 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:44:48,546 - root - INFO - Doing fitness calculating with individual {\"id\":\"73f976f2-7c71-4dba-8aa5-3319506e8cd1\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[16,28306.322419768014,24459.67703105131]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[22,-34.375016823222836,115.26143335105144]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.4320638940882422,0.6983689680006248,0.14492820643337656]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:44:48,547 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:44:52,888 - root - INFO - Training is complete\n", + "2024-06-09 23:44:53,363 - root - INFO - Wow! all topics\n", + "2024-06-09 23:44:53,364 - root - INFO - Building dictionary\n", + "2024-06-09 23:44:53,950 - root - INFO - COMPONENTS 3.589711300356379 2.0848260707647883\n", + "2024-06-09 23:44:54,543 - root - INFO - Fitness estimation took 6.00\n", + "2024-06-09 23:44:55,030 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:44:55,031 - root - INFO - Doing fitness calculating with individual {\"id\":\"0e766c7a-3eb6-4c6e-9494-fe9c5f4d21e7\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[21,45829.36234007214,97615.94599645167]},{\"stage_type\":{\"name\":\"SmoothThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SmoothPhi\",\"distribution\":{\"low\":0.0,\"high\":100.0}},{\"name\":\"SmoothTheta\",\"distribution\":{\"low\":0.0,\"high\":100.0}}]},\"values\":[22,21.020877459080268,52.185056618541694]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:44:55,032 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:44:58,881 - root - INFO - Training is complete\n", + "2024-06-09 23:44:59,259 - root - INFO - Building dictionary\n", + "2024-06-09 23:44:59,576 - root - INFO - COMPONENTS 0.002155580089565534 0.0\n", + "2024-06-09 23:44:59,878 - root - INFO - Fitness estimation took 4.85\n", + "2024-06-09 23:45:00,161 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:45:00,162 - root - INFO - Doing fitness calculating with individual {\"id\":\"4d3e409d-3bc3-4605-92c8-dbc4e8bd76e5\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[22,-34.375016823222836,115.26143335105144]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:45:00,163 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:45:01,729 - root - INFO - Training is complete\n", + "2024-06-09 23:45:01,981 - root - INFO - Wow! all topics\n", + "2024-06-09 23:45:01,982 - root - INFO - Building dictionary\n", + "2024-06-09 23:45:02,237 - root - INFO - COMPONENTS 6.086138635602913 5.574308278289958\n", + "2024-06-09 23:45:02,576 - root - INFO - Fitness estimation took 2.41\n", + "2024-06-09 23:45:02,911 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:45:02,912 - root - INFO - Doing fitness calculating with individual {\"id\":\"2796fe22-c64d-4c2a-8ef8-5de40928a95c\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[30,922.8651352529662,-58.61765505286655]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[27,-459.1118336821203,807.2130291495512]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.6065560125611166,0.6935414883927496,0.25846351499899267]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:45:02,913 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:45:08,759 - root - INFO - Training is complete\n", + "2024-06-09 23:45:09,649 - root - INFO - Wow! all topics\n", + "2024-06-09 23:45:09,651 - root - INFO - Building dictionary\n", + "2024-06-09 23:45:10,549 - root - INFO - COMPONENTS 6.098993344782298 5.087681900614781\n", + "2024-06-09 23:45:11,527 - root - INFO - Fitness estimation took 8.61\n", + "2024-06-09 23:45:12,067 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:45:12,068 - root - INFO - Doing fitness calculating with individual {\"id\":\"34a3d6ed-d800-4cd1-902b-4e90228f1c0d\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SmoothThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SmoothPhi\",\"distribution\":{\"low\":0.0,\"high\":100.0}},{\"name\":\"SmoothTheta\",\"distribution\":{\"low\":0.0,\"high\":100.0}}]},\"values\":[3,72.83059407449582,10.973736616243212]},{\"stage_type\":{\"name\":\"SmoothThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SmoothPhi\",\"distribution\":{\"low\":0.0,\"high\":100.0}},{\"name\":\"SmoothTheta\",\"distribution\":{\"low\":0.0,\"high\":100.0}}]},\"values\":[14,63.64481080932214,82.41699206987002]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[22,-34.375016823222836,115.26143335105144]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.11594366356714769,0.7162910207031723,0.5403193180252248]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:45:12,069 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:45:14,210 - root - INFO - Training is complete\n", + "2024-06-09 23:45:14,517 - root - INFO - Wow! all topics\n", + "2024-06-09 23:45:14,518 - root - INFO - Building dictionary\n", + "2024-06-09 23:45:14,873 - root - INFO - COMPONENTS 4.7873987595394745 3.3617591153847814\n", + "2024-06-09 23:45:15,283 - root - INFO - Fitness estimation took 3.21\n", + "2024-06-09 23:45:15,650 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:45:15,652 - root - INFO - Doing fitness calculating with individual {\"id\":\"51650293-6350-4c29-b993-ba1588a4a6e0\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:45:15,652 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:45:18,568 - root - INFO - Training is complete\n", + "2024-06-09 23:45:19,019 - root - INFO - Wow! all topics\n", + "2024-06-09 23:45:19,020 - root - INFO - Building dictionary\n", + "2024-06-09 23:45:19,458 - root - INFO - COMPONENTS 6.184780842365817 5.8981057732722135\n", + "2024-06-09 23:45:19,994 - root - INFO - Fitness estimation took 4.34\n", + "2024-06-09 23:45:20,391 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:45:20,392 - root - INFO - Doing fitness calculating with individual {\"id\":\"217af252-d866-467e-b33a-cde8db5292d0\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[29,13903.182802145775,81046.9666409797]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[11,-240.53586906391695,182.81867960257932]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:45:20,393 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:45:24,137 - root - INFO - Training is complete\n", + "2024-06-09 23:45:24,601 - root - INFO - Building dictionary\n", + "2024-06-09 23:45:25,036 - root - INFO - COMPONENTS 0.30152816261381954 0.0\n", + "2024-06-09 23:45:25,472 - root - INFO - Fitness estimation took 5.08\n", + "2024-06-09 23:45:25,778 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:45:25,779 - root - INFO - Doing fitness calculating with individual {\"id\":\"18c9c389-fa17-48b5-bd5b-f946f521f4a5\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[9,12196.549501486432,43649.390246445604]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[22,-34.375016823222836,115.26143335105144]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.019306010651074845,0.432779596112597,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:45:25,780 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:45:29,432 - root - INFO - Training is complete\n", + "2024-06-09 23:45:29,860 - root - INFO - Wow! all topics\n", + "2024-06-09 23:45:29,861 - root - INFO - Building dictionary\n", + "2024-06-09 23:45:30,384 - root - INFO - COMPONENTS 3.972758828414133 2.4552580419109646\n", + "2024-06-09 23:45:30,932 - root - INFO - Fitness estimation took 5.15\n", + "2024-06-09 23:45:31,415 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:45:31,416 - root - INFO - Doing fitness calculating with individual {\"id\":\"52faf335-711e-40d9-b080-b27b0fd866d8\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[22,-34.375016823222836,115.26143335105144]},{\"stage_type\":{\"name\":\"SmoothThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SmoothPhi\",\"distribution\":{\"low\":0.0,\"high\":100.0}},{\"name\":\"SmoothTheta\",\"distribution\":{\"low\":0.0,\"high\":100.0}}]},\"values\":[3,72.83059407449582,10.973736616243212]},{\"stage_type\":{\"name\":\"SmoothThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SmoothPhi\",\"distribution\":{\"low\":0.0,\"high\":100.0}},{\"name\":\"SmoothTheta\",\"distribution\":{\"low\":0.0,\"high\":100.0}}]},\"values\":[14,63.64481080932214,82.41699206987002]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.5403193180252248]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:45:31,417 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:45:36,376 - root - INFO - Training is complete\n", + "2024-06-09 23:45:37,139 - root - INFO - Wow! all topics\n", + "2024-06-09 23:45:37,140 - root - INFO - Building dictionary\n", + "2024-06-09 23:45:37,959 - root - INFO - COMPONENTS 5.768777694389541 4.4001650497767555\n", + "2024-06-09 23:45:38,806 - root - INFO - Fitness estimation took 7.39\n", + "2024-06-09 23:45:39,353 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:45:39,354 - root - INFO - Doing fitness calculating with individual {\"id\":\"d266e7d2-036e-4680-92a0-6a8d9045f832\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[24,93536.13282614859,15161.50047514564]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[27,-465.63938098423273,395.89126481683525]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.7775349387076155]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:45:39,355 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:45:43,483 - root - INFO - Training is complete\n", + "2024-06-09 23:45:43,824 - root - INFO - Building dictionary\n", + "2024-06-09 23:45:44,108 - root - INFO - COMPONENTS 0.0 0\n", + "2024-06-09 23:45:44,371 - root - INFO - Fitness estimation took 5.02\n", + "2024-06-09 23:45:44,625 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:45:44,626 - root - INFO - Doing fitness calculating with individual {\"id\":\"dd6b6cbf-1ec4-4670-a7bd-ce1bb5c0c901\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[22,-34.375016823222836,115.26143335105144]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.4497499961826149,0.11207492014222842,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:45:44,627 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:45:47,197 - root - INFO - Training is complete\n", + "2024-06-09 23:45:47,619 - root - INFO - Wow! all topics\n", + "2024-06-09 23:45:47,620 - root - INFO - Building dictionary\n", + "2024-06-09 23:45:48,026 - root - INFO - COMPONENTS 6.097095125177168 5.526486782341623\n", + "2024-06-09 23:45:48,522 - root - INFO - Fitness estimation took 3.90\n", + "2024-06-09 23:45:48,920 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:45:48,922 - root - INFO - Doing fitness calculating with individual {\"id\":\"d609c5ce-1be9-4990-8e30-0e4f4576fb08\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[19,-351.96733800853644,-500.9700674033861]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:45:48,922 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:45:49,882 - root - INFO - Training is complete\n", + "2024-06-09 23:45:49,967 - root - INFO - Building dictionary\n", + "2024-06-09 23:45:50,004 - root - INFO - COMPONENTS 0.0 0\n", + "2024-06-09 23:45:50,024 - root - INFO - Fitness estimation took 1.10\n", + "2024-06-09 23:45:50,209 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:45:50,210 - root - INFO - Doing fitness calculating with individual {\"id\":\"da2d617c-30f2-4d41-843e-c80bf3c07f05\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[5,747.8930389408683,766.7776636941433]},{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[27,70478.07499700676,85491.70314354691]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[22,-34.375016823222836,115.26143335105144]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.22454255072543772,0.41073732308251054,0.5402265081116119]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:45:50,211 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:45:56,005 - root - INFO - Training is complete\n", + "2024-06-09 23:45:56,235 - root - INFO - Building dictionary\n", + "2024-06-09 23:45:56,417 - root - INFO - COMPONENTS 0.0004259479387816416 0.0\n", + "2024-06-09 23:45:56,580 - root - INFO - Fitness estimation took 6.37\n", + "2024-06-09 23:45:56,817 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:45:56,818 - root - INFO - Doing fitness calculating with individual {\"id\":\"166f5968-8d6b-419a-a477-ec7dd6cbf655\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:45:56,819 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:45:57,322 - root - INFO - Training is complete\n", + "2024-06-09 23:45:57,446 - root - INFO - Wow! all topics\n", + "2024-06-09 23:45:57,447 - root - INFO - Building dictionary\n", + "2024-06-09 23:45:57,539 - root - INFO - COMPONENTS 6.1777531320435655 5.82923675666261\n", + "2024-06-09 23:45:57,744 - root - INFO - Fitness estimation took 0.92\n", + "2024-06-09 23:45:58,036 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:45:58,037 - root - INFO - Doing fitness calculating with individual {\"id\":\"d9e5184f-e261-47e7-86f5-f6e0b75be2ed\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[9,12196.549501486432,43649.390246445604]},{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[29,13903.182802145775,81046.9666409797]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[11,-240.53586906391695,182.81867960257932]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[30,922.8651352529662,-58.61765505286655]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[27,-459.1118336821203,807.2130291495512]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.019306010651074845,0.432779596112597,0.25846351499899267]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:45:58,038 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:46:04,658 - root - INFO - Training is complete\n", + "2024-06-09 23:46:05,355 - root - INFO - Building dictionary\n", + "2024-06-09 23:46:06,190 - root - INFO - COMPONENTS 3.3300679647105293 0.0\n", + "2024-06-09 23:46:06,959 - root - INFO - Fitness estimation took 8.92\n", + "2024-06-09 23:46:07,507 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:46:07,508 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:46:07,509 - GA_algo - INFO - size of the new generation is 19\n", + "2024-06-09 23:46:07,510 - GA_algo - INFO - CROSSOVER IS OVER\n", + "2024-06-09 23:46:07,874 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:46:07,875 - root - INFO - Doing fitness calculating with individual {\"id\":\"4b06dba4-e6d7-42db-80a9-290ff08b59d6\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[7,-334.3018253454877,503.0033770985847]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.5411522054698827,0.25846351499899267]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:46:07,876 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:46:08,249 - root - INFO - Training is complete\n", + "2024-06-09 23:46:08,359 - root - INFO - Wow! all topics\n", + "2024-06-09 23:46:08,360 - root - INFO - Building dictionary\n", + "2024-06-09 23:46:08,439 - root - INFO - COMPONENTS 6.185235481709425 5.82923675666261\n", + "2024-06-09 23:46:08,634 - root - INFO - Fitness estimation took 0.76\n", + "2024-06-09 23:46:08,903 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:46:08,904 - root - INFO - Doing fitness calculating with individual {\"id\":\"4d557f97-7d6e-4eac-8411-e03b09416f9f\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:46:08,905 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:46:09,991 - root - INFO - Training is complete\n", + "2024-06-09 23:46:10,188 - root - INFO - Wow! all topics\n", + "2024-06-09 23:46:10,189 - root - INFO - Building dictionary\n", + "2024-06-09 23:46:10,348 - root - INFO - COMPONENTS 6.181216033990913 5.885853870558686\n", + "2024-06-09 23:46:10,621 - root - INFO - Fitness estimation took 1.72\n", + "2024-06-09 23:46:10,923 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:46:10,924 - root - INFO - Doing fitness calculating with individual {\"id\":\"b136f704-f2df-47de-863a-b09ba313a6df\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[22,-34.375016823222836,115.26143335105144]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.4497499961826149,0.11207492014222842,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:46:10,925 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:46:13,492 - root - INFO - Training is complete\n", + "2024-06-09 23:46:13,895 - root - INFO - Wow! all topics\n", + "2024-06-09 23:46:13,896 - root - INFO - Building dictionary\n", + "2024-06-09 23:46:14,286 - root - INFO - COMPONENTS 6.097095125177168 5.526486782341623\n", + "2024-06-09 23:46:14,777 - root - INFO - Fitness estimation took 3.85\n", + "2024-06-09 23:46:15,167 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:46:15,168 - root - INFO - Doing fitness calculating with individual {\"id\":\"96ea23e7-0920-45a4-8be3-c4dfcd1f6cef\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[22,-34.375016823222836,115.26143335105144]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:46:15,169 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:46:19,162 - root - INFO - Training is complete\n", + "2024-06-09 23:46:19,767 - root - INFO - Wow! all topics\n", + "2024-06-09 23:46:19,768 - root - INFO - Building dictionary\n", + "2024-06-09 23:46:20,360 - root - INFO - COMPONENTS 6.046833051729624 5.440896700285236\n", + "2024-06-09 23:46:21,089 - root - INFO - Fitness estimation took 5.92\n", + "2024-06-09 23:46:21,551 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:46:21,553 - root - INFO - Doing fitness calculating with individual {\"id\":\"82810ae9-3013-4154-839c-4ea0937d3802\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[30,922.8651352529662,-58.61765505286655]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[27,-459.1118336821203,807.2130291495512]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.806346131375872,0.27797165579110483,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:46:21,553 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:46:24,902 - root - INFO - Training is complete\n", + "2024-06-09 23:46:25,412 - root - INFO - Wow! all topics\n", + "2024-06-09 23:46:25,413 - root - INFO - Building dictionary\n", + "2024-06-09 23:46:25,907 - root - INFO - COMPONENTS 6.123550028296587 5.361724229217961\n", + "2024-06-09 23:46:26,494 - root - INFO - Fitness estimation took 4.94\n", + "2024-06-09 23:46:26,916 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:46:26,917 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:46:26,918 - GA_algo - INFO - MUTATION IS OVER\n", + "2024-06-09 23:46:26,918 - GA_algo - INFO - Population len 11. Best params so far: pipeline=Pipeline(stages=[Stage(stage_type=StageType(name='SparseThetaRegularizer', params=[Param(name='n', distribution=IntRangeDistribution(low=1, high=30)), Param(name='SparsePhi', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0)), Param(name='SparseTheta', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0))]), values=[28, 141.03533054556738, 395.82369455306207]), Stage(stage_type=StageType(name='SparseThetaRegularizer', params=[Param(name='n', distribution=IntRangeDistribution(low=1, high=30)), Param(name='SparsePhi', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0)), Param(name='SparseTheta', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0))]), values=[28, 868.2703427609019, 2.2980766899298715])], required_params=Stage(stage_type=StageType(name='General', params=[Param(name='basic_topics_count', distribution=IntRangeDistribution(low=0, high=5)), Param(name='ext_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_elem_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_mutation_selector', distribution=FloatRangeDistribution(low=0.0, high=1.0))]), values=[4, 0.983741321427002, 0.8513219009715824, 0.15592682911863887])), with fitness: 12.082886615638031.ITERATION TIME: 118.34730243682861DATASET __noname__.TOPICS NUM 25.RUN ID ee461a46-d514-43d0-952a-8b6c87bc1818.\n", + "2024-06-09 23:46:26,919 - root - INFO - Sending a best individual to be logged\n", + "2024-06-09 23:46:26,920 - root - INFO - Doing fitness calculating with individual {\"id\":\"51650293-6350-4c29-b993-ba1588a4a6e0\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":{\"avg_coherence_score\":12.082886615638031,\"perplexityScore\":1354.903564453125,\"backgroundTokensRatioScore\":0.07008196413516998,\"contrast\":0.0,\"purity\":0.0,\"kernelSize\":0.0,\"npmi_50_list\":null,\"npmi_50\":null,\"sparsity_phi\":0.0,\"sparsity_theta\":0.0,\"topic_significance_uni\":null,\"topic_significance_vacuous\":null,\"topic_significance_back\":null,\"switchP_list\":[NaN],\"switchP\":NaN,\"all_topics\":true,\"coherence_10_list\":[6.7858301321066845,6.819704125587706,6.81015328161727,6.781480270718103,6.776942765596009,6.415694418173987,6.511511499453723,6.782087644950563,6.701378569528666,6.856104842127825,6.715258904023472,6.906832410962406,6.811515675783815,6.784559318540944,6.71502212100932,6.917367857924916,6.698414702271158,6.991365593236741,6.723793753535029,6.907165820793223,6.855182938882594,6.705875024615536,6.736505993320824,6.436080993913767,6.6851361642719755],\"coherence_10\":6.7532385929178504,\"coherence_15_list\":[6.533259130184876,6.7434837491616255,6.676293077333751,6.622572816911698,6.634785696596073,6.543250772340982,6.807546066213145,6.728711461158361,6.838639592375927,6.806680003129368,6.613986826696021,6.761203755026397,6.717342134701923,6.865286380988009,6.50350987427352,6.7682790606570125,6.70023925043501,6.691226140354909,6.7053840788376515,6.668008457557747,6.787711817480437,6.389919473877501,6.501393967308763,6.636975246871754,6.659785673774253],\"coherence_15\":6.676218980169868,\"coherence_20_list\":[6.440435133189408,6.659106257405973,6.55089693627856,6.6455190172386125,6.5790086960063405,6.5947683102246994,6.700962359282933,6.7127281194044235,6.798792616089414,6.699997856014576,6.718095271814978,6.700824302398949,6.773251697451521,6.803760917706244,6.619669001130016,6.821728357084125,6.573961657039193,6.571372577724315,6.640206956571774,6.635693031269097,6.666153713359492,6.564475729543362,6.4162418298363715,6.502651391963986,6.718571003168363],\"coherence_20\":6.644354909567869,\"coherence_25_list\":[6.437688380848758,6.59966394892218,6.630403748877013,6.690951976281171,6.493275751881386,6.512721723012499,6.481866674051389,6.71522859851743,6.796677108539224,6.5988511561993475,6.672880461019763,6.3965785649630185,6.598355429358399,6.593455515152737,6.515019948150179,6.686675395110283,6.61575982148018,6.549396149552706,6.549399570310933,6.508441929441296,6.5788085660430635,6.565638385343294,6.437685500704231,6.482272836867887,6.643303621334244],\"coherence_25\":6.574040030478503,\"coherence_30_list\":[6.482098918978516,6.548243466297207,6.548272959642934,6.572057095606508,6.400159054311371,6.4632215579161825,6.366237072750015,6.57281588480168,6.6321274967375015,6.538956654187582,6.602900565945083,6.391969437680232,6.410563569872653,6.442432592661131,6.424760108261033,6.650657461481903,6.598103637604241,6.506266149086785,6.545742598298266,6.471190406939862,6.537517365463286,6.453327180016858,6.390883366171085,6.509473125337747,6.475900806786466],\"coherence_30\":6.501435141313444,\"coherence_35_list\":[6.4324237865686635,6.504259127082547,6.4409895200263705,6.450987144912491,6.380285538188899,6.3707681446752185,6.3597393966721,6.509476144196142,6.513373983566715,6.417394427334757,6.437859139213484,6.380971100588271,6.42972999537857,6.416686281175656,6.391256217156042,6.431467593380564,6.417285456823313,6.475720152854428,6.44640694132154,6.3916975588672695,6.335064410274765,6.329266676424064,6.393654130714744,6.46725023408537,6.3350606270154675],\"coherence_35\":6.418362949139898,\"coherence_40_list\":[6.314088533899338,6.440888689958535,6.286380210957718,6.315410185531957,6.3521725420876685,6.2948979856765614,6.2368732564007585,6.4818170273893765,6.359430740216728,6.343806992738206,6.387165109423469,6.299686299423515,6.356827066066335,6.362227863519711,6.346686100426116,6.352020912707191,6.339019494837858,6.447718935516403,6.333661579009238,6.360940016243175,6.1709106498351165,6.323418246916633,6.085375040254289,6.39240699542377,6.241554452277762],\"coherence_40\":6.329015397069498,\"coherence_45_list\":[6.207906894546949,6.428046278855477,6.267066446518198,6.242048472495815,6.3127840133526165,6.246819369242941,6.214270131561679,6.225946391561108,6.3776602965056,6.329173915511055,6.288183855311328,6.159866928809343,6.309053280097041,6.342890825737377,6.295999946539268,6.389625536749416,6.250240430466953,6.406281204363509,6.2710564600552985,6.291615347521038,6.116533505771055,6.2171264685550085,6.023045209049441,6.227933339333337,6.203831850241904],\"coherence_45\":6.26580025595011,\"coherence_50_list\":[6.136433633792123,6.372238671731571,6.239947269495553,6.143621098820163,6.0802964423210675,6.183130371097223,6.061092944824211,6.227699618196113,6.327832805112076,6.249835854475267,6.268067942999083,6.089609345921891,6.194266284100646,6.158195228342677,6.195574572460845,6.298767750175846,6.167246220655687,6.307407459290226,6.215546867826738,6.170445765877084,6.102428118119738,6.195007413809493,5.8981057732722135,6.225437705648406,6.111285900779486],\"coherence_50\":6.184780842365817,\"coherence_55_list\":[6.110695877855694,6.330017067415392,6.209242603080784,6.11254170515144,5.994516722457159,6.134685346318044,6.006657054139613,6.07990959848731,6.236554409235719,6.185135647755921,6.129934918506294,5.902262586690597,6.0596954213233465,6.01365117587213,6.061664619070946,6.110255189298392,6.048035822891773,6.146689579475568,6.090882517661938,6.101737058557582,6.016086632057962,6.072900822653465,5.77981894703448,6.133718208522051,6.15671894909748],\"coherence_55\":6.088960339224443,\"npmi_15\":null,\"npmi_25\":null},\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":0,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:46:26,921 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:46:29,785 - root - INFO - Training is complete\n", + "2024-06-09 23:46:30,229 - root - INFO - Wow! all topics\n", + "2024-06-09 23:46:30,230 - root - INFO - Building dictionary\n", + "2024-06-09 23:46:30,650 - root - INFO - COMPONENTS 6.184780842365817 5.8981057732722135\n", + "2024-06-09 23:46:31,175 - root - INFO - Fitness estimation took 4.25\n", + "2024-06-09 23:46:31,513 - root - INFO - Logging params and artifacts to mlflow\n", + "2024-06-09 23:46:31,513 - root - INFO - Created experiment_0\n", + "2024-06-09 23:46:31,543 - root - INFO - Experiment exists, omitting creation\n", + "2024-06-09 23:46:31,544 - root - INFO - Experiment run name: fitness-__noname__-238bd98d-6f51-4634-b62c-80d75b82d9ed_tmp_0\n", + "2024-06-09 23:46:31,641 - git.cmd - DEBUG - Popen(['git', 'version'], cwd=/notebooks/autotm, stdin=None, shell=False, universal_newlines=False)\n", + "2024-06-09 23:46:31,742 - git.cmd - DEBUG - Popen(['git', 'version'], cwd=/notebooks/autotm, stdin=None, shell=False, universal_newlines=False)\n", + "2024-06-09 23:46:31,822 - root - DEBUG - Params dict: {'0_General_basic_topics_count': 4, '0_General_ext_mutation_prob': 0.983741321427002, '0_General_ext_elem_mutation_prob': 0.8513219009715824, '0_General_ext_mutation_selector': 0.15592682911863887, '1_SparseThetaRegularizer_n': 28, '1_SparseThetaRegularizer_SparsePhi': 141.03533054556738, '1_SparseThetaRegularizer_SparseTheta': 395.82369455306207, '2_SparseThetaRegularizer_n': 28, '2_SparseThetaRegularizer_SparsePhi': 868.2703427609019, '2_SparseThetaRegularizer_SparseTheta': 2.2980766899298715}\n", + "2024-06-09 23:46:32,695 - root - INFO - Logged params and artifacts to mlflow\n", + "2024-06-09 23:46:32,757 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:46:32,757 - GA_algo - INFO - ENTERING GENERATION 1\n", + "2024-06-09 23:46:32,758 - GA_algo - INFO - PAIRS ARE CREATED\n", + "2024-06-09 23:46:32,768 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:46:32,769 - root - INFO - Doing fitness calculating with individual {\"id\":\"1c074932-5a85-4451-9f68-b80f02708251\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:46:32,770 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:46:34,825 - root - INFO - Training is complete\n", + "2024-06-09 23:46:35,157 - root - INFO - Wow! all topics\n", + "2024-06-09 23:46:35,158 - root - INFO - Building dictionary\n", + "2024-06-09 23:46:35,465 - root - INFO - COMPONENTS 6.177241647042988 5.885853870558686\n", + "2024-06-09 23:46:35,875 - root - INFO - Fitness estimation took 3.11\n", + "2024-06-09 23:46:36,230 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:46:36,231 - root - INFO - Doing fitness calculating with individual {\"id\":\"551042bf-4e53-49ab-acf8-98cb347361d1\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:46:36,232 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:46:38,173 - root - INFO - Training is complete\n", + "2024-06-09 23:46:38,459 - root - INFO - Wow! all topics\n", + "2024-06-09 23:46:38,460 - root - INFO - Building dictionary\n", + "2024-06-09 23:46:38,719 - root - INFO - COMPONENTS 6.166244471316852 5.722915632358659\n", + "2024-06-09 23:46:39,090 - root - INFO - Fitness estimation took 2.86\n", + "2024-06-09 23:46:39,418 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:46:39,419 - root - INFO - Doing fitness calculating with individual {\"id\":\"5c2c8a77-5695-49f1-afc8-978c7264d5e9\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:46:39,419 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:46:40,027 - root - INFO - Training is complete\n", + "2024-06-09 23:46:40,178 - root - INFO - Wow! all topics\n", + "2024-06-09 23:46:40,179 - root - INFO - Building dictionary\n", + "2024-06-09 23:46:40,285 - root - INFO - COMPONENTS 6.180834003352823 5.94613194631003\n", + "2024-06-09 23:46:40,501 - root - INFO - Fitness estimation took 1.08\n", + "2024-06-09 23:46:40,803 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:46:40,805 - root - INFO - Doing fitness calculating with individual {\"id\":\"900e0dca-ffc2-45cb-9f51-c75647d05351\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:46:40,805 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:46:41,814 - root - INFO - Training is complete\n", + "2024-06-09 23:46:42,000 - root - INFO - Wow! all topics\n", + "2024-06-09 23:46:42,001 - root - INFO - Building dictionary\n", + "2024-06-09 23:46:42,152 - root - INFO - COMPONENTS 6.183683641102923 5.917344732418264\n", + "2024-06-09 23:46:42,409 - root - INFO - Fitness estimation took 1.60\n", + "2024-06-09 23:46:42,699 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:46:42,700 - root - INFO - Doing fitness calculating with individual {\"id\":\"d3ed2da7-82ba-4753-ba9c-31ba40a46f85\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.983741321427002,0.27797165579110483,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:46:42,701 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:46:44,641 - root - INFO - Training is complete\n", + "2024-06-09 23:46:44,960 - root - INFO - Wow! all topics\n", + "2024-06-09 23:46:44,962 - root - INFO - Building dictionary\n", + "2024-06-09 23:46:45,259 - root - INFO - COMPONENTS 6.18527947756429 5.8981057732722135\n", + "2024-06-09 23:46:45,648 - root - INFO - Fitness estimation took 2.95\n", + "2024-06-09 23:46:46,001 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:46:46,002 - root - INFO - Doing fitness calculating with individual {\"id\":\"0e621d8d-5858-4481-b7a7-9aa8dca60a4a\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[30,922.8651352529662,-58.61765505286655]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[27,-459.1118336821203,807.2130291495512]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.806346131375872,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:46:46,003 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:46:50,359 - root - INFO - Training is complete\n", + "2024-06-09 23:46:51,014 - root - INFO - Wow! all topics\n", + "2024-06-09 23:46:51,015 - root - INFO - Building dictionary\n", + "2024-06-09 23:46:51,651 - root - INFO - COMPONENTS 6.149532145563109 5.381725782985908\n", + "2024-06-09 23:46:52,376 - root - INFO - Fitness estimation took 6.37\n", + "2024-06-09 23:46:52,842 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:46:52,843 - root - INFO - Doing fitness calculating with individual {\"id\":\"e2b02ce0-86e4-4cb8-9b67-5c5fb93b12e2\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[19,50313.67078879694,16532.243853954322]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.5411522054698827,0.7779445107555456]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:46:52,843 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:46:55,350 - root - INFO - Training is complete\n", + "2024-06-09 23:46:55,690 - root - INFO - Building dictionary\n", + "2024-06-09 23:46:55,972 - root - INFO - COMPONENTS 0.0 0.0\n", + "2024-06-09 23:46:56,241 - root - INFO - Fitness estimation took 3.40\n", + "2024-06-09 23:46:56,513 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:46:56,514 - root - INFO - Doing fitness calculating with individual {\"id\":\"c76de7c5-065f-4c58-8265-95932e6d9270\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.3833948468508369,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:46:56,515 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:46:57,925 - root - INFO - Training is complete\n", + "2024-06-09 23:46:58,160 - root - INFO - Wow! all topics\n", + "2024-06-09 23:46:58,161 - root - INFO - Building dictionary\n", + "2024-06-09 23:46:58,366 - root - INFO - COMPONENTS 6.176668917991531 5.854526196544299\n", + "2024-06-09 23:46:58,677 - root - INFO - Fitness estimation took 2.16\n", + "2024-06-09 23:46:58,994 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:46:58,995 - root - INFO - Doing fitness calculating with individual {\"id\":\"01c8905b-d6fd-4849-8d28-e5aa5a875ad8\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:46:58,996 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:47:00,456 - root - INFO - Training is complete\n", + "2024-06-09 23:47:00,723 - root - INFO - Wow! all topics\n", + "2024-06-09 23:47:00,724 - root - INFO - Building dictionary\n", + "2024-06-09 23:47:00,954 - root - INFO - COMPONENTS 6.169403230192717 5.885853870558686\n", + "2024-06-09 23:47:01,290 - root - INFO - Fitness estimation took 2.29\n", + "2024-06-09 23:47:01,635 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:47:01,636 - root - INFO - Doing fitness calculating with individual {\"id\":\"ba3c7144-fc00-474c-b9c3-f6b1a2ef67a8\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[19,50313.67078879694,16532.243853954322]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.3833948468508369,0.5411522054698827,0.7779445107555456]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:47:01,637 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:47:04,610 - root - INFO - Training is complete\n", + "2024-06-09 23:47:04,965 - root - INFO - Wow! all topics\n", + "2024-06-09 23:47:04,965 - root - INFO - Building dictionary\n", + "2024-06-09 23:47:05,383 - root - INFO - COMPONENTS 3.1209059915197357 1.7046524664781175\n", + "2024-06-09 23:47:05,861 - root - INFO - Fitness estimation took 4.22\n", + "2024-06-09 23:47:06,253 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:47:06,254 - root - INFO - Doing fitness calculating with individual {\"id\":\"b83e72fd-b5ef-4dcc-ae93-b710f3b4fef8\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[19,50313.67078879694,16532.243853954322]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:47:06,255 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:47:10,184 - root - INFO - Training is complete\n", + "2024-06-09 23:47:10,722 - root - INFO - Building dictionary\n", + "2024-06-09 23:47:11,193 - root - INFO - COMPONENTS 0.0015001565871553778 0.0\n", + "2024-06-09 23:47:11,649 - root - INFO - Fitness estimation took 5.39\n", + "2024-06-09 23:47:11,970 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:47:11,971 - root - INFO - Doing fitness calculating with individual {\"id\":\"e74ba80d-a735-452b-823f-29535274ff90\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.983741321427002,0.5411522054698827,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:47:11,972 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:47:12,479 - root - INFO - Training is complete\n", + "2024-06-09 23:47:12,605 - root - INFO - Wow! all topics\n", + "2024-06-09 23:47:12,606 - root - INFO - Building dictionary\n", + "2024-06-09 23:47:12,704 - root - INFO - COMPONENTS 6.1777531320435655 5.82923675666261\n", + "2024-06-09 23:47:12,910 - root - INFO - Fitness estimation took 0.94\n", + "2024-06-09 23:47:13,180 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:47:13,181 - root - INFO - Doing fitness calculating with individual {\"id\":\"2eb63915-6a07-4463-9f0e-7c60516f5f26\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[19,50313.67078879694,16532.243853954322]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.3833948468508369,0.8513219009715824,0.7779445107555456]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:47:13,182 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:47:15,114 - root - INFO - Training is complete\n", + "2024-06-09 23:47:15,363 - root - INFO - Wow! all topics\n", + "2024-06-09 23:47:15,364 - root - INFO - Building dictionary\n", + "2024-06-09 23:47:15,652 - root - INFO - COMPONENTS 3.2294910527576075 1.7702242646612056\n", + "2024-06-09 23:47:16,016 - root - INFO - Fitness estimation took 2.83\n", + "2024-06-09 23:47:16,333 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:47:16,334 - root - INFO - Doing fitness calculating with individual {\"id\":\"65a735c3-9ca7-4eea-ba77-809999b7a62b\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SmoothThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SmoothPhi\",\"distribution\":{\"low\":0.0,\"high\":100.0}},{\"name\":\"SmoothTheta\",\"distribution\":{\"low\":0.0,\"high\":100.0}}]},\"values\":[3,72.83059407449582,10.973736616243212]},{\"stage_type\":{\"name\":\"SmoothThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SmoothPhi\",\"distribution\":{\"low\":0.0,\"high\":100.0}},{\"name\":\"SmoothTheta\",\"distribution\":{\"low\":0.0,\"high\":100.0}}]},\"values\":[14,63.64481080932214,82.41699206987002]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.11594366356714769,0.7162910207031723,0.5403193180252248]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:47:16,335 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:47:20,327 - root - INFO - Training is complete\n", + "2024-06-09 23:47:20,837 - root - INFO - Wow! all topics\n", + "2024-06-09 23:47:20,838 - root - INFO - Building dictionary\n", + "2024-06-09 23:47:21,461 - root - INFO - COMPONENTS 4.614789423803161 3.504753298209214\n", + "2024-06-09 23:47:22,071 - root - INFO - Fitness estimation took 5.74\n", + "2024-06-09 23:47:22,554 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:47:22,555 - root - INFO - Doing fitness calculating with individual {\"id\":\"67d36ad1-6819-4b09-86c4-6f0023617c22\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[30,922.8651352529662,-58.61765505286655]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[27,-459.1118336821203,807.2130291495512]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.4497499961826149,0.11207492014222842,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:47:22,556 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:47:27,449 - root - INFO - Training is complete\n", + "2024-06-09 23:47:28,190 - root - INFO - Wow! all topics\n", + "2024-06-09 23:47:28,191 - root - INFO - Building dictionary\n", + "2024-06-09 23:47:28,914 - root - INFO - COMPONENTS 6.093467427589631 4.9616605916565435\n", + "2024-06-09 23:47:29,733 - root - INFO - Fitness estimation took 7.18\n", + "2024-06-09 23:47:30,231 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:47:30,233 - root - INFO - Doing fitness calculating with individual {\"id\":\"2ae6ca6b-7038-4fb0-a57d-b0ca046e3d3f\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[22,-34.375016823222836,115.26143335105144]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.806346131375872,0.27797165579110483,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:47:30,234 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:47:31,442 - root - INFO - Training is complete\n", + "2024-06-09 23:47:31,651 - root - INFO - Wow! all topics\n", + "2024-06-09 23:47:31,652 - root - INFO - Building dictionary\n", + "2024-06-09 23:47:31,841 - root - INFO - COMPONENTS 6.0944264557639976 5.550619718317753\n", + "2024-06-09 23:47:32,129 - root - INFO - Fitness estimation took 1.90\n", + "2024-06-09 23:47:32,450 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:47:32,451 - root - INFO - Doing fitness calculating with individual {\"id\":\"91954ede-7f68-4e1a-a685-503f826fdd22\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:47:32,451 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:47:35,047 - root - INFO - Training is complete\n", + "2024-06-09 23:47:35,447 - root - INFO - Wow! all topics\n", + "2024-06-09 23:47:35,448 - root - INFO - Building dictionary\n", + "2024-06-09 23:47:35,834 - root - INFO - COMPONENTS 6.188618610860698 5.917344732418264\n", + "2024-06-09 23:47:36,315 - root - INFO - Fitness estimation took 3.86\n", + "2024-06-09 23:47:36,699 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:47:36,700 - root - INFO - Doing fitness calculating with individual {\"id\":\"53de550c-7d56-43b4-8718-f3153b4943c9\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:47:36,701 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:47:38,065 - root - INFO - Training is complete\n", + "2024-06-09 23:47:38,292 - root - INFO - Wow! all topics\n", + "2024-06-09 23:47:38,293 - root - INFO - Building dictionary\n", + "2024-06-09 23:47:38,487 - root - INFO - COMPONENTS 6.182390564804042 5.852301534971088\n", + "2024-06-09 23:47:38,796 - root - INFO - Fitness estimation took 2.09\n", + "2024-06-09 23:47:39,107 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:47:39,108 - root - INFO - Doing fitness calculating with individual {\"id\":\"a9a3a290-a3f8-43b2-9a6e-291a0c719df7\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[5,0.4516736916170343,0.6149157124782801,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:47:39,108 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:47:40,603 - root - INFO - Training is complete\n", + "2024-06-09 23:47:40,861 - root - INFO - Wow! all topics\n", + "2024-06-09 23:47:40,862 - root - INFO - Building dictionary\n", + "2024-06-09 23:47:41,098 - root - INFO - COMPONENTS 6.175792415342114 5.854526196544299\n", + "2024-06-09 23:47:41,433 - root - INFO - Fitness estimation took 2.32\n", + "2024-06-09 23:47:41,770 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:47:41,771 - root - INFO - Doing fitness calculating with individual {\"id\":\"9d4c890b-95fa-45ba-b0a8-5dcb20fe2d4f\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[22,-34.375016823222836,115.26143335105144]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:47:41,771 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:47:44,454 - root - INFO - Training is complete\n", + "2024-06-09 23:47:44,855 - root - INFO - Wow! all topics\n", + "2024-06-09 23:47:44,856 - root - INFO - Building dictionary\n", + "2024-06-09 23:47:45,265 - root - INFO - COMPONENTS 6.086522552893877 5.526486782341622\n", + "2024-06-09 23:47:45,765 - root - INFO - Fitness estimation took 3.99\n", + "2024-06-09 23:47:46,172 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:47:46,172 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:47:46,173 - GA_algo - INFO - size of the new generation is 20\n", + "2024-06-09 23:47:46,174 - GA_algo - INFO - CROSSOVER IS OVER\n", + "2024-06-09 23:47:46,520 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:47:46,522 - root - INFO - Doing fitness calculating with individual {\"id\":\"1ef50bac-9416-4130-9171-7e5057fbfd50\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[17,-454.7867338065066,101.71838031200355]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:47:46,522 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:47:49,270 - root - INFO - Training is complete\n", + "2024-06-09 23:47:49,561 - root - INFO - Building dictionary\n", + "2024-06-09 23:47:49,789 - root - INFO - COMPONENTS 0.0 0\n", + "2024-06-09 23:47:49,993 - root - INFO - Fitness estimation took 3.47\n", + "2024-06-09 23:47:50,253 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:47:50,254 - root - INFO - Doing fitness calculating with individual {\"id\":\"a405d503-f215-4896-ae32-52580473b4d8\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[25,647.2894098811125,-497.3106501492548]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:47:50,255 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:47:51,965 - root - INFO - Training is complete\n", + "2024-06-09 23:47:52,233 - root - INFO - Wow! all topics\n", + "2024-06-09 23:47:52,234 - root - INFO - Building dictionary\n", + "2024-06-09 23:47:52,491 - root - INFO - COMPONENTS 6.0893934888687555 5.113253300551372\n", + "2024-06-09 23:47:52,842 - root - INFO - Fitness estimation took 2.59\n", + "2024-06-09 23:47:53,181 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:47:53,182 - root - INFO - Doing fitness calculating with individual {\"id\":\"2e84800f-5d4c-46eb-a417-842b3ce84bdb\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.9865394404766477,0.27797165579110483,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:47:53,183 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:47:55,058 - root - INFO - Training is complete\n", + "2024-06-09 23:47:55,351 - root - INFO - Wow! all topics\n", + "2024-06-09 23:47:55,352 - root - INFO - Building dictionary\n", + "2024-06-09 23:47:55,616 - root - INFO - COMPONENTS 6.18527947756429 5.8981057732722135\n", + "2024-06-09 23:47:55,986 - root - INFO - Fitness estimation took 2.80\n", + "2024-06-09 23:47:56,314 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:47:56,315 - root - INFO - Doing fitness calculating with individual {\"id\":\"b71757d6-ca54-4715-a9fa-6bc6fceabcbe\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.7281045725666423,0.46738007747537214,0.736608505349805]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:47:56,316 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:47:59,155 - root - INFO - Training is complete\n", + "2024-06-09 23:47:59,576 - root - INFO - Wow! all topics\n", + "2024-06-09 23:47:59,577 - root - INFO - Building dictionary\n", + "2024-06-09 23:47:59,969 - root - INFO - COMPONENTS 6.184780842365817 5.8981057732722135\n", + "2024-06-09 23:48:00,469 - root - INFO - Fitness estimation took 4.15\n", + "2024-06-09 23:48:00,854 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:00,855 - root - INFO - Doing fitness calculating with individual {\"id\":\"5cf8cd93-1d84-4ef8-8644-7896357c58c6\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-334.3018253454877,87.1697349203771]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:00,856 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:02,243 - root - INFO - Training is complete\n", + "2024-06-09 23:48:02,317 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:02,323 - root - INFO - COMPONENTS 0.0 0\n", + "2024-06-09 23:48:02,326 - root - INFO - Fitness estimation took 1.47\n", + "2024-06-09 23:48:02,491 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:02,492 - root - INFO - Doing fitness calculating with individual {\"id\":\"dfc2e7e9-2d50-43b8-a100-670432487503\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[5,0.2653884364897948,0.8513219009715824,0.7914820796771036]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:02,492 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:04,602 - root - INFO - Training is complete\n", + "2024-06-09 23:48:04,944 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:04,945 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:05,264 - root - INFO - COMPONENTS 6.177241647042988 5.885853870558686\n", + "2024-06-09 23:48:05,688 - root - INFO - Fitness estimation took 3.20\n", + "2024-06-09 23:48:06,054 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:06,055 - root - INFO - Doing fitness calculating with individual {\"id\":\"5ea2ba72-2377-4703-9535-67d81c3c44e5\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-834.7151313686312,886.8906854929398]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:06,055 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:06,901 - root - INFO - Training is complete\n", + "2024-06-09 23:48:07,077 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:07,077 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:07,238 - root - INFO - COMPONENTS 6.156961516805338 5.685994217878482\n", + "2024-06-09 23:48:07,496 - root - INFO - Fitness estimation took 1.44\n", + "2024-06-09 23:48:07,807 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:07,808 - root - INFO - Doing fitness calculating with individual {\"id\":\"68e82d17-21cb-4798-b5b4-ea8cf37dec33\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:07,809 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:08,840 - root - INFO - Training is complete\n", + "2024-06-09 23:48:09,030 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:09,031 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:09,190 - root - INFO - COMPONENTS 6.182406147784217 5.885853870558685\n", + "2024-06-09 23:48:09,455 - root - INFO - Fitness estimation took 1.65\n", + "2024-06-09 23:48:09,758 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:09,759 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:48:09,760 - GA_algo - INFO - MUTATION IS OVER\n", + "2024-06-09 23:48:09,761 - GA_algo - INFO - Population len 11. Best params so far: pipeline=Pipeline(stages=[Stage(stage_type=StageType(name='SparseThetaRegularizer', params=[Param(name='n', distribution=IntRangeDistribution(low=1, high=30)), Param(name='SparsePhi', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0)), Param(name='SparseTheta', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0))]), values=[12, 862.6766687279264, 135.15287388864226])], required_params=Stage(stage_type=StageType(name='General', params=[Param(name='basic_topics_count', distribution=IntRangeDistribution(low=0, high=5)), Param(name='ext_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_elem_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_mutation_selector', distribution=FloatRangeDistribution(low=0.0, high=1.0))]), values=[0, 0.6065560125611166, 0.6935414883927496, 0.4825868764489578])), with fitness: 12.126965949662853.ITERATION TIME: 97.00343585014343DATASET __noname__.TOPICS NUM 25.RUN ID ee461a46-d514-43d0-952a-8b6c87bc1818.\n", + "2024-06-09 23:48:09,761 - root - INFO - Sending a best individual to be logged\n", + "2024-06-09 23:48:09,762 - root - INFO - Doing fitness calculating with individual {\"id\":\"5c2c8a77-5695-49f1-afc8-978c7264d5e9\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":{\"avg_coherence_score\":12.126965949662853,\"perplexityScore\":1367.0140380859375,\"backgroundTokensRatioScore\":0.05860655754804611,\"contrast\":0.0,\"purity\":0.0,\"kernelSize\":0.0,\"npmi_50_list\":null,\"npmi_50\":null,\"sparsity_phi\":0.0,\"sparsity_theta\":0.0,\"topic_significance_uni\":null,\"topic_significance_vacuous\":null,\"topic_significance_back\":null,\"switchP_list\":[NaN],\"switchP\":NaN,\"all_topics\":true,\"coherence_10_list\":[6.847273399192251,6.730724307314206,6.81015328161727,6.781480270718103,6.77694276559601,6.415694418173986,6.5402244804936425,6.782087644950563,6.701378569528667,6.856104842127825,6.715258904023474,6.906832410962406,6.805157772835139,6.784559318540944,6.71502212100932,6.917367857924914,6.698414702271158,6.991365593236741,6.723793753535029,6.907165820793221,6.855182938882594,6.705875024615536,6.736505993320824,6.436080993913767,6.685136164271975],\"coherence_10\":6.753031333993983,\"coherence_15_list\":[6.533259130184876,6.7434837491616255,6.676293077333751,6.622572816911698,6.634785696596075,6.524346738566347,6.807546066213145,6.815954094691511,6.616734862340504,6.806680003129368,6.7020103275216725,6.761203755026397,6.717342134701922,6.8652863809880085,6.50350987427352,6.7755456749933485,6.60972623815657,6.706803361581337,6.70538407883765,6.668008457557744,6.787711817480435,6.382209451443663,6.501393967308762,6.636975246871754,6.661356405379554],\"coherence_15\":6.67064493629005,\"coherence_20_list\":[6.543529778298098,6.659106257405972,6.55089693627856,6.601624053428274,6.477956477788523,6.584763982393815,6.656955728438524,6.712728119404426,6.725730382236146,6.699997856014576,6.718095271814978,6.702235053167015,6.847602816557056,6.783694536761621,6.496320847180677,6.8217283570841225,6.573961657039192,6.615320972439311,6.640206956571775,6.635693031269098,6.601603508474884,6.564475729543362,6.402111263533532,6.540205951744872,6.718571003168364],\"coherence_20\":6.635004661121472,\"coherence_25_list\":[6.4562658078034,6.59966394892218,6.630403748877014,6.690951976281171,6.488971781028378,6.577738053891906,6.523056981418214,6.723446755987442,6.718751309089274,6.5988511561993475,6.653573921873519,6.449681069821281,6.749235806281429,6.670130443377854,6.515019948150179,6.644008902225608,6.548021815408342,6.6152028000627165,6.50265717472447,6.585544502416424,6.5788085660430635,6.556676378307134,6.432315960631782,6.482272836867887,6.570576649251297],\"coherence_25\":6.582473131797652,\"coherence_30_list\":[6.498301850613089,6.522535683163357,6.49412486825226,6.572057095606508,6.4021018511757735,6.46322155791618,6.416418018786766,6.612127580417481,6.660997116306298,6.538956654187582,6.5562471519261605,6.430528212033041,6.465225422306231,6.466394285190932,6.441010902849499,6.589092563683,6.598103637604237,6.554074123829485,6.521299828945756,6.4539040677744,6.555482680895484,6.557706911577103,6.423998047441563,6.473138026882254,6.397376493040208],\"coherence_30\":6.506576985296187,\"coherence_35_list\":[6.403993328955538,6.462154149778253,6.440989520026369,6.4165717176204735,6.344841496274747,6.370768144675219,6.324671198303996,6.551281980225318,6.444174891534814,6.417394427334757,6.437859139213485,6.324413395987504,6.374993912044886,6.452615949237499,6.391256217156041,6.5181892514292326,6.419554682954688,6.51480769332043,6.4332619550790024,6.392868815504892,6.450582928822726,6.408463110518769,6.220838899490337,6.448118184151123,6.308714264986353],\"coherence_35\":6.410935170185058,\"coherence_40_list\":[6.30776544475684,6.440888689958534,6.393979992768134,6.297851305062039,6.322423057973425,6.239924453458568,6.3006782655132785,6.4747793056016185,6.3901285235578875,6.431380765162843,6.387165109423467,6.2123813395574,6.338190936249873,6.286209005533212,6.344914954513021,6.428270985096164,6.358408527484597,6.447132442119591,6.364551711901957,6.3073312319138894,6.1900493234735325,6.248089748961348,6.175713956500994,6.387114894051671,6.205720811567557],\"coherence_40\":6.331241791286456,\"coherence_45_list\":[6.196164221994946,6.351691112650757,6.3876871616475634,6.2169367259764,6.2700687095415955,6.154446551697229,6.17751286550516,6.497909083831898,6.350876703135634,6.353290419225084,6.273368257422746,6.10877835770136,6.125628963460158,6.163246233493589,6.285113911098988,6.387130315208957,6.27931548552275,6.413741896156556,6.239117383936755,6.292372700874718,6.092104690588711,6.243802338228963,6.118583431499146,6.301566496512477,6.146092099903227],\"coherence_45\":6.257061844672615,\"coherence_50_list\":[6.148699935315383,6.326911028321904,6.239947269495553,6.184194116344167,6.213987750895649,6.154614045231385,6.101080248667447,6.408587979920304,6.254104246981741,6.249013718990919,6.265822702728159,6.0037499668126015,6.018770607969764,6.1650329870269305,6.180272942662255,6.25422435765407,6.166204569308145,6.334086157926717,6.170494242529895,6.236511466949228,6.050193270336161,6.1273842321012815,5.94613194631003,6.209544392561376,6.111285900779486],\"coherence_50\":6.180834003352823,\"coherence_55_list\":[6.153647478055628,6.28603684260796,6.212023155321504,6.1382169485543345,6.074421697343837,6.104739726572959,6.051968223883241,6.169135553843967,6.195168094416744,6.242748775556229,6.199417846435927,5.9910717059339165,6.025975591178977,6.014461955408583,6.089510694517783,6.102852534309653,6.113577271330549,6.245489116366203,6.099461673251516,6.111546243466477,5.994337079709307,6.072900822653464,5.803431514985174,6.111547412573434,6.055213608917615],\"coherence_55\":6.1063560626878,\"npmi_15\":null,\"npmi_25\":null},\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":1,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:09,763 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:10,359 - root - INFO - Training is complete\n", + "2024-06-09 23:48:10,497 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:10,498 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:10,601 - root - INFO - COMPONENTS 6.180834003352823 5.94613194631003\n", + "2024-06-09 23:48:10,818 - root - INFO - Fitness estimation took 1.05\n", + "2024-06-09 23:48:11,037 - root - INFO - Logging params and artifacts to mlflow\n", + "2024-06-09 23:48:11,038 - root - INFO - Created experiment_0\n", + "2024-06-09 23:48:11,056 - root - INFO - Experiment exists, omitting creation\n", + "2024-06-09 23:48:11,057 - root - INFO - Experiment run name: fitness-__noname__-25e2b278-4233-4f45-82c9-06f8238c5708_tmp_1\n", + "2024-06-09 23:48:11,131 - root - DEBUG - Params dict: {'0_General_basic_topics_count': 0, '0_General_ext_mutation_prob': 0.6065560125611166, '0_General_ext_elem_mutation_prob': 0.6935414883927496, '0_General_ext_mutation_selector': 0.4825868764489578, '1_SparseThetaRegularizer_n': 12, '1_SparseThetaRegularizer_SparsePhi': 862.6766687279264, '1_SparseThetaRegularizer_SparseTheta': 135.15287388864226}\n", + "2024-06-09 23:48:11,674 - root - INFO - Logged params and artifacts to mlflow\n", + "2024-06-09 23:48:11,730 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:11,731 - GA_algo - INFO - ENTERING GENERATION 2\n", + "2024-06-09 23:48:11,731 - GA_algo - INFO - PAIRS ARE CREATED\n", + "2024-06-09 23:48:11,743 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:48:11,744 - root - INFO - Doing fitness calculating with individual {\"id\":\"6f9a0fcb-5359-4a71-aa5c-2c87cd1a9203\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.9865394404766477,0.27797165579110483,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:11,744 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:12,253 - root - INFO - Training is complete\n", + "2024-06-09 23:48:12,382 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:12,383 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:12,481 - root - INFO - COMPONENTS 6.1731571940594385 5.885853870558686\n", + "2024-06-09 23:48:12,687 - root - INFO - Fitness estimation took 0.94\n", + "2024-06-09 23:48:12,965 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:12,966 - root - INFO - Doing fitness calculating with individual {\"id\":\"efbac60f-bcae-462b-b8f8-a2248b006608\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:12,966 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:14,901 - root - INFO - Training is complete\n", + "2024-06-09 23:48:15,197 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:15,198 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:15,464 - root - INFO - COMPONENTS 6.18339978047133 5.82923675666261\n", + "2024-06-09 23:48:15,837 - root - INFO - Fitness estimation took 2.87\n", + "2024-06-09 23:48:16,158 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:16,159 - root - INFO - Doing fitness calculating with individual {\"id\":\"6e3a42a4-c6ca-4ac3-829c-5dcc11fbeccc\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:16,160 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:17,778 - root - INFO - Training is complete\n", + "2024-06-09 23:48:18,036 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:18,037 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:18,269 - root - INFO - COMPONENTS 6.169154511093149 5.917344732418264\n", + "2024-06-09 23:48:18,607 - root - INFO - Fitness estimation took 2.45\n", + "2024-06-09 23:48:18,930 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:18,931 - root - INFO - Doing fitness calculating with individual {\"id\":\"1e700b83-8958-4b98-871a-1e17287c9003\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[5,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:18,932 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:19,603 - root - INFO - Training is complete\n", + "2024-06-09 23:48:19,753 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:19,754 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:19,879 - root - INFO - COMPONENTS 6.172440228491896 5.854526196544299\n", + "2024-06-09 23:48:20,107 - root - INFO - Fitness estimation took 1.18\n", + "2024-06-09 23:48:20,408 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:20,409 - root - INFO - Doing fitness calculating with individual {\"id\":\"c2a12683-008a-463f-8fca-079a5c8c2841\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.2653884364897948,0.8513219009715824,0.7914820796771036]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:20,409 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:22,335 - root - INFO - Training is complete\n", + "2024-06-09 23:48:22,632 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:22,633 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:22,898 - root - INFO - COMPONENTS 6.167701085044618 5.854526196544299\n", + "2024-06-09 23:48:23,269 - root - INFO - Fitness estimation took 2.86\n", + "2024-06-09 23:48:23,596 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:23,597 - root - INFO - Doing fitness calculating with individual {\"id\":\"fd45f10e-720c-446b-bfd4-1937a9edd29a\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-834.7151313686312,886.8906854929398]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:23,598 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:25,090 - root - INFO - Training is complete\n", + "2024-06-09 23:48:25,352 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:25,353 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:25,599 - root - INFO - COMPONENTS 6.148077891537797 5.701265502259485\n", + "2024-06-09 23:48:25,938 - root - INFO - Fitness estimation took 2.34\n", + "2024-06-09 23:48:26,288 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:26,289 - root - INFO - Doing fitness calculating with individual {\"id\":\"465e2165-4492-4023-848f-1e574840f323\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.46738007747537214,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:26,290 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:29,709 - root - INFO - Training is complete\n", + "2024-06-09 23:48:30,212 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:30,213 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:30,701 - root - INFO - COMPONENTS 6.18712599885963 5.8981057732722135\n", + "2024-06-09 23:48:31,280 - root - INFO - Fitness estimation took 4.99\n", + "2024-06-09 23:48:31,694 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:31,695 - root - INFO - Doing fitness calculating with individual {\"id\":\"6bb31b61-468c-4845-b9a0-bca5ecdf3a65\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:31,696 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:33,315 - root - INFO - Training is complete\n", + "2024-06-09 23:48:33,579 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:33,580 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:33,815 - root - INFO - COMPONENTS 6.187896925587603 5.917344732418264\n", + "2024-06-09 23:48:34,149 - root - INFO - Fitness estimation took 2.45\n", + "2024-06-09 23:48:34,473 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:34,474 - root - INFO - Doing fitness calculating with individual {\"id\":\"f6e918e0-c476-4154-a243-893057067f5e\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-834.7151313686312,886.8906854929398]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[4,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:34,475 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:37,288 - root - INFO - Training is complete\n", + "2024-06-09 23:48:37,720 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:37,721 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:38,169 - root - INFO - COMPONENTS 5.981587338463064 5.22969247120446\n", + "2024-06-09 23:48:38,688 - root - INFO - Fitness estimation took 4.21\n", + "2024-06-09 23:48:39,141 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:39,142 - root - INFO - Doing fitness calculating with individual {\"id\":\"fd0d8b33-90a7-4a74-b862-fdb98dccd4db\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.7281045725666423,0.46738007747537214,0.736608505349805]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:39,143 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:42,540 - root - INFO - Training is complete\n", + "2024-06-09 23:48:43,035 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:43,036 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:43,514 - root - INFO - COMPONENTS 6.188957533238761 5.917344732418264\n", + "2024-06-09 23:48:44,086 - root - INFO - Fitness estimation took 4.94\n", + "2024-06-09 23:48:44,493 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:44,494 - root - INFO - Doing fitness calculating with individual {\"id\":\"0a79f3bb-072f-4f58-b815-fb5420ca7754\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[5,0.2653884364897948,0.8513219009715824,0.7914820796771036]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:44,495 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:45,988 - root - INFO - Training is complete\n", + "2024-06-09 23:48:46,248 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:46,249 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:46,483 - root - INFO - COMPONENTS 6.175792415342114 5.854526196544299\n", + "2024-06-09 23:48:46,817 - root - INFO - Fitness estimation took 2.32\n", + "2024-06-09 23:48:47,149 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:47,150 - root - INFO - Doing fitness calculating with individual {\"id\":\"2d1ce9e9-6efb-42f7-b297-8a595f369d09\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:47,151 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:48,325 - root - INFO - Training is complete\n", + "2024-06-09 23:48:48,528 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:48,529 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:48,708 - root - INFO - COMPONENTS 6.181608210338693 5.8523015349710885\n", + "2024-06-09 23:48:48,998 - root - INFO - Fitness estimation took 1.85\n", + "2024-06-09 23:48:49,321 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:49,322 - root - INFO - Doing fitness calculating with individual {\"id\":\"fa8a95c6-588f-4cbd-8048-2e8c98db23d7\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[5,0.2653884364897948,0.8513219009715824,0.7914820796771036]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:49,323 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:50,805 - root - INFO - Training is complete\n", + "2024-06-09 23:48:51,067 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:51,068 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:51,301 - root - INFO - COMPONENTS 6.169403230192717 5.885853870558686\n", + "2024-06-09 23:48:51,643 - root - INFO - Fitness estimation took 2.32\n", + "2024-06-09 23:48:51,979 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:51,980 - root - INFO - Doing fitness calculating with individual {\"id\":\"79c46938-8a12-4a4f-aaaa-9852ed9b3c22\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.8513219009715824,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:51,980 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:52,599 - root - INFO - Training is complete\n", + "2024-06-09 23:48:52,737 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:52,740 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:52,851 - root - INFO - COMPONENTS 6.180834003352823 5.94613194631003\n", + "2024-06-09 23:48:53,068 - root - INFO - Fitness estimation took 1.09\n", + "2024-06-09 23:48:53,348 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:53,349 - root - INFO - Doing fitness calculating with individual {\"id\":\"7db83c3e-9a75-4db2-9ef2-1d0ada357fb3\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[5,0.2653884364897948,0.6935414883927496,0.7914820796771036]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:53,349 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:55,526 - root - INFO - Training is complete\n", + "2024-06-09 23:48:55,871 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:55,872 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:56,191 - root - INFO - COMPONENTS 6.177241647042988 5.885853870558686\n", + "2024-06-09 23:48:56,609 - root - INFO - Fitness estimation took 3.26\n", + "2024-06-09 23:48:56,974 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:56,975 - root - INFO - Doing fitness calculating with individual {\"id\":\"80f919fb-00a9-4f18-ad57-ceb7469e6944\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.7281045725666423,0.46738007747537214,0.736608505349805]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:56,976 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:48:58,416 - root - INFO - Training is complete\n", + "2024-06-09 23:48:58,656 - root - INFO - Wow! all topics\n", + "2024-06-09 23:48:58,657 - root - INFO - Building dictionary\n", + "2024-06-09 23:48:58,868 - root - INFO - COMPONENTS 6.169403230192717 5.885853870558686\n", + "2024-06-09 23:48:59,184 - root - INFO - Fitness estimation took 2.21\n", + "2024-06-09 23:48:59,500 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:48:59,501 - root - INFO - Doing fitness calculating with individual {\"id\":\"b696a6cb-85bb-4292-a048-97f24e5cd8b2\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.9865394404766477,0.27797165579110483,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:48:59,502 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:49:02,813 - root - INFO - Training is complete\n", + "2024-06-09 23:49:03,285 - root - INFO - Wow! all topics\n", + "2024-06-09 23:49:03,286 - root - INFO - Building dictionary\n", + "2024-06-09 23:49:03,737 - root - INFO - COMPONENTS 6.186497795581801 5.917344732418264\n", + "2024-06-09 23:49:04,290 - root - INFO - Fitness estimation took 4.79\n", + "2024-06-09 23:49:04,685 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:49:04,686 - root - INFO - Doing fitness calculating with individual {\"id\":\"b25af619-62b8-4125-81e8-8c28cc00dc1d\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.9865394404766477,0.27797165579110483,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:49:04,687 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:49:05,705 - root - INFO - Training is complete\n", + "2024-06-09 23:49:05,893 - root - INFO - Wow! all topics\n", + "2024-06-09 23:49:05,894 - root - INFO - Building dictionary\n", + "2024-06-09 23:49:06,051 - root - INFO - COMPONENTS 6.174281831276338 5.917344732418264\n", + "2024-06-09 23:49:06,316 - root - INFO - Fitness estimation took 1.63\n", + "2024-06-09 23:49:06,619 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:49:06,620 - root - INFO - Doing fitness calculating with individual {\"id\":\"58f39009-ea62-408c-ae0c-cc9f8dbd7e24\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[25,647.2894098811125,-497.3106501492548]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.983741321427002,0.8513219009715824,0.15592682911863887]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:49:06,620 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:49:09,235 - root - INFO - Training is complete\n", + "2024-06-09 23:49:09,629 - root - INFO - Wow! all topics\n", + "2024-06-09 23:49:09,630 - root - INFO - Building dictionary\n", + "2024-06-09 23:49:10,001 - root - INFO - COMPONENTS 6.059084343105344 4.624158194907494\n", + "2024-06-09 23:49:10,458 - root - INFO - Fitness estimation took 3.84\n", + "2024-06-09 23:49:10,859 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:49:10,860 - root - INFO - Doing fitness calculating with individual {\"id\":\"4077e63f-849b-4d06-a07c-588e686e5c8b\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[7,-334.3018253454877,503.0033770985847]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:49:10,861 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:49:11,908 - root - INFO - Training is complete\n", + "2024-06-09 23:49:12,089 - root - INFO - Wow! all topics\n", + "2024-06-09 23:49:12,090 - root - INFO - Building dictionary\n", + "2024-06-09 23:49:12,245 - root - INFO - COMPONENTS 6.181111785196854 5.82923675666261\n", + "2024-06-09 23:49:12,499 - root - INFO - Fitness estimation took 1.64\n", + "2024-06-09 23:49:12,782 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:49:12,783 - root - INFO - Doing fitness calculating with individual {\"id\":\"1e3a8aad-a5b4-4ac9-a1c4-94163d3df5b5\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[22,-34.375016823222836,115.26143335105144]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.7281045725666423,0.6149157124782801,0.736608505349805]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:49:12,784 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:49:16,756 - root - INFO - Training is complete\n", + "2024-06-09 23:49:17,319 - root - INFO - Wow! all topics\n", + "2024-06-09 23:49:17,320 - root - INFO - Building dictionary\n", + "2024-06-09 23:49:17,888 - root - INFO - COMPONENTS 6.042926253023251 5.440896700285236\n", + "2024-06-09 23:49:18,536 - root - INFO - Fitness estimation took 5.75\n", + "2024-06-09 23:49:18,985 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:49:18,986 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:49:18,987 - GA_algo - INFO - size of the new generation is 21\n", + "2024-06-09 23:49:18,987 - GA_algo - INFO - CROSSOVER IS OVER\n", + "2024-06-09 23:49:19,274 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:49:19,275 - root - INFO - Doing fitness calculating with individual {\"id\":\"bc459ffa-595f-4023-8a3f-20082563bdc1\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:49:19,276 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:49:22,668 - root - INFO - Training is complete\n", + "2024-06-09 23:49:23,163 - root - INFO - Wow! all topics\n", + "2024-06-09 23:49:23,164 - root - INFO - Building dictionary\n", + "2024-06-09 23:49:23,641 - root - INFO - COMPONENTS 6.188957533238761 5.917344732418264\n", + "2024-06-09 23:49:24,216 - root - INFO - Fitness estimation took 4.94\n", + "2024-06-09 23:49:24,623 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:49:24,624 - root - INFO - Doing fitness calculating with individual {\"id\":\"c2c04cd2-9b40-4af8-809c-57c0e4dcdcfb\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,223.90038767793067,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.9865394404766477,0.27797165579110483,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:49:24,624 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:49:27,979 - root - INFO - Training is complete\n", + "2024-06-09 23:49:28,472 - root - INFO - Wow! all topics\n", + "2024-06-09 23:49:28,473 - root - INFO - Building dictionary\n", + "2024-06-09 23:49:28,922 - root - INFO - COMPONENTS 6.097304561045883 5.099469433280663\n", + "2024-06-09 23:49:29,471 - root - INFO - Fitness estimation took 4.85\n", + "2024-06-09 23:49:29,886 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:49:29,887 - root - INFO - Doing fitness calculating with individual {\"id\":\"4722fd3d-63db-465e-b088-4e10672195d9\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,-23.961907253498907]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.9865394404766477,0.27797165579110483,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:49:29,887 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:49:30,860 - root - INFO - Training is complete\n", + "2024-06-09 23:49:30,991 - root - INFO - Building dictionary\n", + "2024-06-09 23:49:31,063 - root - INFO - COMPONENTS 0.0 0\n", + "2024-06-09 23:49:31,125 - root - INFO - Fitness estimation took 1.24\n", + "2024-06-09 23:49:31,305 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:49:31,306 - root - INFO - Doing fitness calculating with individual {\"id\":\"3f1ac324-b360-4ab1-9225-56c1926c203a\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.9865394404766477,0.27797165579110483,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:49:31,307 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:49:33,341 - root - INFO - Training is complete\n", + "2024-06-09 23:49:33,646 - root - INFO - Wow! all topics\n", + "2024-06-09 23:49:33,647 - root - INFO - Building dictionary\n", + "2024-06-09 23:49:33,927 - root - INFO - COMPONENTS 6.185876585935856 5.8981057732722135\n", + "2024-06-09 23:49:34,302 - root - INFO - Fitness estimation took 3.00\n", + "2024-06-09 23:49:34,646 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:49:34,647 - root - INFO - Doing fitness calculating with individual {\"id\":\"d4de7636-3ec2-4d0d-a1c4-04c4d1926f41\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,-14.933439151692824,19.433010230222976]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.7281045725666423,0.46738007747537214,0.736608505349805]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:49:34,648 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:49:36,729 - root - INFO - Training is complete\n", + "2024-06-09 23:49:37,061 - root - INFO - Wow! all topics\n", + "2024-06-09 23:49:37,062 - root - INFO - Building dictionary\n", + "2024-06-09 23:49:37,414 - root - INFO - COMPONENTS 5.121432764198846 3.9938469403098127\n", + "2024-06-09 23:49:37,834 - root - INFO - Fitness estimation took 3.19\n", + "2024-06-09 23:49:38,248 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:49:38,249 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:49:38,250 - GA_algo - INFO - MUTATION IS OVER\n", + "2024-06-09 23:49:38,251 - GA_algo - INFO - Population len 11. Best params so far: pipeline=Pipeline(stages=[Stage(stage_type=StageType(name='SparseThetaRegularizer', params=[Param(name='n', distribution=IntRangeDistribution(low=1, high=30)), Param(name='SparsePhi', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0)), Param(name='SparseTheta', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0))]), values=[12, 862.6766687279264, 135.15287388864226])], required_params=Stage(stage_type=StageType(name='General', params=[Param(name='basic_topics_count', distribution=IntRangeDistribution(low=0, high=5)), Param(name='ext_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_elem_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_mutation_selector', distribution=FloatRangeDistribution(low=0.0, high=1.0))]), values=[0, 0.6065560125611166, 0.6935414883927496, 0.4825868764489578])), with fitness: 12.126965949662853.ITERATION TIME: 86.52054715156555DATASET __noname__.TOPICS NUM 25.RUN ID ee461a46-d514-43d0-952a-8b6c87bc1818.\n", + "2024-06-09 23:49:38,252 - root - INFO - Sending a best individual to be logged\n", + "2024-06-09 23:49:38,253 - root - INFO - Doing fitness calculating with individual {\"id\":\"5c2c8a77-5695-49f1-afc8-978c7264d5e9\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":{\"avg_coherence_score\":12.126965949662853,\"perplexityScore\":1367.0140380859375,\"backgroundTokensRatioScore\":0.05860655754804611,\"contrast\":0.0,\"purity\":0.0,\"kernelSize\":0.0,\"npmi_50_list\":null,\"npmi_50\":null,\"sparsity_phi\":0.0,\"sparsity_theta\":0.0,\"topic_significance_uni\":null,\"topic_significance_vacuous\":null,\"topic_significance_back\":null,\"switchP_list\":[NaN],\"switchP\":NaN,\"all_topics\":true,\"coherence_10_list\":[6.847273399192251,6.730724307314206,6.81015328161727,6.781480270718103,6.77694276559601,6.415694418173986,6.5402244804936425,6.782087644950563,6.701378569528667,6.856104842127825,6.715258904023474,6.906832410962406,6.805157772835139,6.784559318540944,6.71502212100932,6.917367857924914,6.698414702271158,6.991365593236741,6.723793753535029,6.907165820793221,6.855182938882594,6.705875024615536,6.736505993320824,6.436080993913767,6.685136164271975],\"coherence_10\":6.753031333993983,\"coherence_15_list\":[6.533259130184876,6.7434837491616255,6.676293077333751,6.622572816911698,6.634785696596075,6.524346738566347,6.807546066213145,6.815954094691511,6.616734862340504,6.806680003129368,6.7020103275216725,6.761203755026397,6.717342134701922,6.8652863809880085,6.50350987427352,6.7755456749933485,6.60972623815657,6.706803361581337,6.70538407883765,6.668008457557744,6.787711817480435,6.382209451443663,6.501393967308762,6.636975246871754,6.661356405379554],\"coherence_15\":6.67064493629005,\"coherence_20_list\":[6.543529778298098,6.659106257405972,6.55089693627856,6.601624053428274,6.477956477788523,6.584763982393815,6.656955728438524,6.712728119404426,6.725730382236146,6.699997856014576,6.718095271814978,6.702235053167015,6.847602816557056,6.783694536761621,6.496320847180677,6.8217283570841225,6.573961657039192,6.615320972439311,6.640206956571775,6.635693031269098,6.601603508474884,6.564475729543362,6.402111263533532,6.540205951744872,6.718571003168364],\"coherence_20\":6.635004661121472,\"coherence_25_list\":[6.4562658078034,6.59966394892218,6.630403748877014,6.690951976281171,6.488971781028378,6.577738053891906,6.523056981418214,6.723446755987442,6.718751309089274,6.5988511561993475,6.653573921873519,6.449681069821281,6.749235806281429,6.670130443377854,6.515019948150179,6.644008902225608,6.548021815408342,6.6152028000627165,6.50265717472447,6.585544502416424,6.5788085660430635,6.556676378307134,6.432315960631782,6.482272836867887,6.570576649251297],\"coherence_25\":6.582473131797652,\"coherence_30_list\":[6.498301850613089,6.522535683163357,6.49412486825226,6.572057095606508,6.4021018511757735,6.46322155791618,6.416418018786766,6.612127580417481,6.660997116306298,6.538956654187582,6.5562471519261605,6.430528212033041,6.465225422306231,6.466394285190932,6.441010902849499,6.589092563683,6.598103637604237,6.554074123829485,6.521299828945756,6.4539040677744,6.555482680895484,6.557706911577103,6.423998047441563,6.473138026882254,6.397376493040208],\"coherence_30\":6.506576985296187,\"coherence_35_list\":[6.403993328955538,6.462154149778253,6.440989520026369,6.4165717176204735,6.344841496274747,6.370768144675219,6.324671198303996,6.551281980225318,6.444174891534814,6.417394427334757,6.437859139213485,6.324413395987504,6.374993912044886,6.452615949237499,6.391256217156041,6.5181892514292326,6.419554682954688,6.51480769332043,6.4332619550790024,6.392868815504892,6.450582928822726,6.408463110518769,6.220838899490337,6.448118184151123,6.308714264986353],\"coherence_35\":6.410935170185058,\"coherence_40_list\":[6.30776544475684,6.440888689958534,6.393979992768134,6.297851305062039,6.322423057973425,6.239924453458568,6.3006782655132785,6.4747793056016185,6.3901285235578875,6.431380765162843,6.387165109423467,6.2123813395574,6.338190936249873,6.286209005533212,6.344914954513021,6.428270985096164,6.358408527484597,6.447132442119591,6.364551711901957,6.3073312319138894,6.1900493234735325,6.248089748961348,6.175713956500994,6.387114894051671,6.205720811567557],\"coherence_40\":6.331241791286456,\"coherence_45_list\":[6.196164221994946,6.351691112650757,6.3876871616475634,6.2169367259764,6.2700687095415955,6.154446551697229,6.17751286550516,6.497909083831898,6.350876703135634,6.353290419225084,6.273368257422746,6.10877835770136,6.125628963460158,6.163246233493589,6.285113911098988,6.387130315208957,6.27931548552275,6.413741896156556,6.239117383936755,6.292372700874718,6.092104690588711,6.243802338228963,6.118583431499146,6.301566496512477,6.146092099903227],\"coherence_45\":6.257061844672615,\"coherence_50_list\":[6.148699935315383,6.326911028321904,6.239947269495553,6.184194116344167,6.213987750895649,6.154614045231385,6.101080248667447,6.408587979920304,6.254104246981741,6.249013718990919,6.265822702728159,6.0037499668126015,6.018770607969764,6.1650329870269305,6.180272942662255,6.25422435765407,6.166204569308145,6.334086157926717,6.170494242529895,6.236511466949228,6.050193270336161,6.1273842321012815,5.94613194631003,6.209544392561376,6.111285900779486],\"coherence_50\":6.180834003352823,\"coherence_55_list\":[6.153647478055628,6.28603684260796,6.212023155321504,6.1382169485543345,6.074421697343837,6.104739726572959,6.051968223883241,6.169135553843967,6.195168094416744,6.242748775556229,6.199417846435927,5.9910717059339165,6.025975591178977,6.014461955408583,6.089510694517783,6.102852534309653,6.113577271330549,6.245489116366203,6.099461673251516,6.111546243466477,5.994337079709307,6.072900822653464,5.803431514985174,6.111547412573434,6.055213608917615],\"coherence_55\":6.1063560626878,\"npmi_15\":null,\"npmi_25\":null},\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":2,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:49:38,254 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:49:38,858 - root - INFO - Training is complete\n", + "2024-06-09 23:49:38,998 - root - INFO - Wow! all topics\n", + "2024-06-09 23:49:38,998 - root - INFO - Building dictionary\n", + "2024-06-09 23:49:39,100 - root - INFO - COMPONENTS 6.180834003352823 5.94613194631003\n", + "2024-06-09 23:49:39,318 - root - INFO - Fitness estimation took 1.06\n", + "2024-06-09 23:49:39,539 - root - INFO - Logging params and artifacts to mlflow\n", + "2024-06-09 23:49:39,540 - root - INFO - Created experiment_0\n", + "2024-06-09 23:49:39,559 - root - INFO - Experiment exists, omitting creation\n", + "2024-06-09 23:49:39,560 - root - INFO - Experiment run name: fitness-__noname__-ab65fcf7-bdba-4036-92b7-383a37b42620_tmp_2\n", + "2024-06-09 23:49:39,633 - root - DEBUG - Params dict: {'0_General_basic_topics_count': 0, '0_General_ext_mutation_prob': 0.6065560125611166, '0_General_ext_elem_mutation_prob': 0.6935414883927496, '0_General_ext_mutation_selector': 0.4825868764489578, '1_SparseThetaRegularizer_n': 12, '1_SparseThetaRegularizer_SparsePhi': 862.6766687279264, '1_SparseThetaRegularizer_SparseTheta': 135.15287388864226}\n", + "2024-06-09 23:49:40,181 - root - INFO - Logged params and artifacts to mlflow\n", + "2024-06-09 23:49:40,236 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:49:40,237 - GA_algo - INFO - ENTERING GENERATION 3\n", + "2024-06-09 23:49:40,238 - GA_algo - INFO - PAIRS ARE CREATED\n", + "2024-06-09 23:49:40,249 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:49:40,250 - root - INFO - Doing fitness calculating with individual {\"id\":\"a047338b-9825-4b2a-b8c7-7718dcc3937c\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.9865394404766477,0.27797165579110483,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:49:40,251 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:49:42,884 - root - INFO - Training is complete\n", + "2024-06-09 23:49:43,265 - root - INFO - Wow! all topics\n", + "2024-06-09 23:49:43,266 - root - INFO - Building dictionary\n", + "2024-06-09 23:49:43,629 - root - INFO - COMPONENTS 6.189495747626496 5.917344732418264\n", + "2024-06-09 23:49:44,080 - root - INFO - Fitness estimation took 3.83\n", + "2024-06-09 23:49:44,448 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:49:44,449 - root - INFO - Doing fitness calculating with individual {\"id\":\"981f6f3c-0a58-403d-b904-f66a50c973d6\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.7281045725666423,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:49:44,450 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:49:46,492 - root - INFO - Training is complete\n", + "2024-06-09 23:49:46,806 - root - INFO - Wow! all topics\n", + "2024-06-09 23:49:46,807 - root - INFO - Building dictionary\n", + "2024-06-09 23:49:47,097 - root - INFO - COMPONENTS 6.174182403486132 5.854526196544299\n", + "2024-06-09 23:49:47,491 - root - INFO - Fitness estimation took 3.04\n", + "2024-06-09 23:49:47,838 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:49:47,839 - root - INFO - Doing fitness calculating with individual {\"id\":\"6b09f8e9-5f65-4029-bbe5-060279316411\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,-14.933439151692824,19.433010230222976]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.46738007747537214,0.736608505349805]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:49:47,840 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:49:48,446 - root - INFO - Training is complete\n", + "2024-06-09 23:49:48,585 - root - INFO - Wow! all topics\n", + "2024-06-09 23:49:48,586 - root - INFO - Building dictionary\n", + "2024-06-09 23:49:48,717 - root - INFO - COMPONENTS 5.53033236830413 4.127477561227872\n", + "2024-06-09 23:49:48,947 - root - INFO - Fitness estimation took 1.11\n", + "2024-06-09 23:49:49,234 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:49:49,235 - root - INFO - Doing fitness calculating with individual {\"id\":\"65ca0ee4-5b32-4c82-82bd-00c51b602805\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:49:49,235 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:49:51,421 - root - INFO - Training is complete\n", + "2024-06-09 23:49:51,749 - root - INFO - Wow! all topics\n", + "2024-06-09 23:49:51,750 - root - INFO - Building dictionary\n", + "2024-06-09 23:49:52,050 - root - INFO - COMPONENTS 6.157197321178891 5.6873829945114815\n", + "2024-06-09 23:49:52,455 - root - INFO - Fitness estimation took 3.22\n", + "2024-06-09 23:49:52,812 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:49:52,813 - root - INFO - Doing fitness calculating with individual {\"id\":\"54d841e9-a080-4741-812e-1cccc31f7795\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,-14.933439151692824,19.433010230222976]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.6935414883927496,0.736608505349805]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:49:52,813 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:49:55,467 - root - INFO - Training is complete\n", + "2024-06-09 23:49:55,858 - root - INFO - Wow! all topics\n", + "2024-06-09 23:49:55,858 - root - INFO - Building dictionary\n", + "2024-06-09 23:49:56,285 - root - INFO - COMPONENTS 5.2581954966413464 4.195699841450071\n", + "2024-06-09 23:49:56,776 - root - INFO - Fitness estimation took 3.96\n", + "2024-06-09 23:49:57,217 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:49:57,218 - root - INFO - Doing fitness calculating with individual {\"id\":\"81828956-85c4-4c71-9884-8d69bb044c14\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.27797165579110483,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:49:57,219 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:49:58,653 - root - INFO - Training is complete\n", + "2024-06-09 23:49:58,903 - root - INFO - Wow! all topics\n", + "2024-06-09 23:49:58,904 - root - INFO - Building dictionary\n", + "2024-06-09 23:49:59,102 - root - INFO - COMPONENTS 6.184078364493212 5.852301534971088\n", + "2024-06-09 23:49:59,413 - root - INFO - Fitness estimation took 2.19\n", + "2024-06-09 23:49:59,731 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:49:59,732 - root - INFO - Doing fitness calculating with individual {\"id\":\"9859f6ae-4c27-40de-a5e0-e0e6568ff354\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.9865394404766477,0.6935414883927496,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:49:59,733 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:00,847 - root - INFO - Training is complete\n", + "2024-06-09 23:50:01,046 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:01,047 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:01,215 - root - INFO - COMPONENTS 6.179103347637603 5.885853870558686\n", + "2024-06-09 23:50:01,500 - root - INFO - Fitness estimation took 1.77\n", + "2024-06-09 23:50:01,806 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:01,807 - root - INFO - Doing fitness calculating with individual {\"id\":\"278773c4-c71b-43bf-96cb-25f37dfef698\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,-14.933439151692824,19.433010230222976]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.46738007747537214,0.736608505349805]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:01,808 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:05,374 - root - INFO - Training is complete\n", + "2024-06-09 23:50:05,883 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:05,884 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:06,432 - root - INFO - COMPONENTS 5.229793194569267 4.164403698637322\n", + "2024-06-09 23:50:07,024 - root - INFO - Fitness estimation took 5.22\n", + "2024-06-09 23:50:07,494 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:07,495 - root - INFO - Doing fitness calculating with individual {\"id\":\"d73293bb-1f98-4281-8ead-896f0d53285b\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.20382144321324902,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:07,496 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:10,015 - root - INFO - Training is complete\n", + "2024-06-09 23:50:10,381 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:10,382 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:10,722 - root - INFO - COMPONENTS 6.180889957727971 5.885853870558686\n", + "2024-06-09 23:50:11,173 - root - INFO - Fitness estimation took 3.68\n", + "2024-06-09 23:50:11,532 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:11,533 - root - INFO - Doing fitness calculating with individual {\"id\":\"3feb4a7a-be6c-4fd4-b513-3ec71f31cd04\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:11,533 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:12,970 - root - INFO - Training is complete\n", + "2024-06-09 23:50:13,208 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:13,209 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:13,420 - root - INFO - COMPONENTS 6.169403230192717 5.885853870558686\n", + "2024-06-09 23:50:13,738 - root - INFO - Fitness estimation took 2.20\n", + "2024-06-09 23:50:14,063 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:14,064 - root - INFO - Doing fitness calculating with individual {\"id\":\"a2355b26-b064-466e-86a5-e0dfa8a9e248\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:14,065 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:16,267 - root - INFO - Training is complete\n", + "2024-06-09 23:50:16,596 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:16,597 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:16,896 - root - INFO - COMPONENTS 6.178045255361489 5.917344732418264\n", + "2024-06-09 23:50:17,302 - root - INFO - Fitness estimation took 3.24\n", + "2024-06-09 23:50:17,649 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:17,651 - root - INFO - Doing fitness calculating with individual {\"id\":\"467cb2c1-890d-4404-95ff-ac06da28a8c5\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[5,0.2653884364897948,0.8513219009715824,0.7914820796771036]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:17,651 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:20,370 - root - INFO - Training is complete\n", + "2024-06-09 23:50:20,822 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:20,824 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:21,244 - root - INFO - COMPONENTS 6.18095395500894 5.8981057732722135\n", + "2024-06-09 23:50:21,755 - root - INFO - Fitness estimation took 4.10\n", + "2024-06-09 23:50:22,160 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:22,161 - root - INFO - Doing fitness calculating with individual {\"id\":\"cef80ee9-2506-471e-b40f-b18b3c8c53e3\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:22,162 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:23,351 - root - INFO - Training is complete\n", + "2024-06-09 23:50:23,556 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:23,557 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:23,732 - root - INFO - COMPONENTS 6.181608210338693 5.8523015349710885\n", + "2024-06-09 23:50:24,013 - root - INFO - Fitness estimation took 1.85\n", + "2024-06-09 23:50:24,312 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:24,313 - root - INFO - Doing fitness calculating with individual {\"id\":\"a1db54e9-0b5b-43e6-bcfb-f4626a6decd2\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:24,313 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:25,367 - root - INFO - Training is complete\n", + "2024-06-09 23:50:25,555 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:25,556 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:25,723 - root - INFO - COMPONENTS 6.182406147784217 5.885853870558685\n", + "2024-06-09 23:50:25,991 - root - INFO - Fitness estimation took 1.68\n", + "2024-06-09 23:50:26,294 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:26,295 - root - INFO - Doing fitness calculating with individual {\"id\":\"6ada71f1-11fd-4d83-b9f8-b7746f74d174\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:26,296 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:29,539 - root - INFO - Training is complete\n", + "2024-06-09 23:50:30,002 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:30,003 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:30,462 - root - INFO - COMPONENTS 6.051542290036056 4.859409306405225\n", + "2024-06-09 23:50:30,998 - root - INFO - Fitness estimation took 4.70\n", + "2024-06-09 23:50:31,417 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:31,418 - root - INFO - Doing fitness calculating with individual {\"id\":\"ff958233-8784-4941-bfbe-1a4ab267d7da\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,223.90038767793067,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:31,418 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:34,158 - root - INFO - Training is complete\n", + "2024-06-09 23:50:34,544 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:34,545 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:34,916 - root - INFO - COMPONENTS 6.150575559106228 5.507385395197843\n", + "2024-06-09 23:50:35,389 - root - INFO - Fitness estimation took 3.97\n", + "2024-06-09 23:50:35,762 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:35,763 - root - INFO - Doing fitness calculating with individual {\"id\":\"0ee8b850-d66e-47ab-88f7-da841db75ea0\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.9865394404766477,0.27797165579110483,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:35,764 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:36,876 - root - INFO - Training is complete\n", + "2024-06-09 23:50:37,111 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:37,112 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:37,280 - root - INFO - COMPONENTS 6.179103347637603 5.885853870558686\n", + "2024-06-09 23:50:37,555 - root - INFO - Fitness estimation took 1.79\n", + "2024-06-09 23:50:37,855 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:37,856 - root - INFO - Doing fitness calculating with individual {\"id\":\"d3bb709e-f962-4ef4-b5e6-cd00a1fdd053\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:37,857 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:38,885 - root - INFO - Training is complete\n", + "2024-06-09 23:50:39,071 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:39,072 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:39,227 - root - INFO - COMPONENTS 6.182406147784217 5.885853870558685\n", + "2024-06-09 23:50:39,492 - root - INFO - Fitness estimation took 1.63\n", + "2024-06-09 23:50:39,784 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:39,785 - root - INFO - Doing fitness calculating with individual {\"id\":\"4a80285a-cc5b-4a80-9156-2917e11f43b8\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:39,786 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:40,969 - root - INFO - Training is complete\n", + "2024-06-09 23:50:41,173 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:41,174 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:41,345 - root - INFO - COMPONENTS 6.181608210338693 5.8523015349710885\n", + "2024-06-09 23:50:41,629 - root - INFO - Fitness estimation took 1.84\n", + "2024-06-09 23:50:41,931 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:41,932 - root - INFO - Doing fitness calculating with individual {\"id\":\"8b81fed9-5502-468b-bb7f-85c3b2ef8b4a\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:41,933 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:43,558 - root - INFO - Training is complete\n", + "2024-06-09 23:50:43,816 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:43,817 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:44,046 - root - INFO - COMPONENTS 6.169154511093149 5.917344732418264\n", + "2024-06-09 23:50:44,384 - root - INFO - Fitness estimation took 2.45\n", + "2024-06-09 23:50:44,712 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:44,713 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:50:44,714 - GA_algo - INFO - size of the new generation is 20\n", + "2024-06-09 23:50:44,715 - GA_algo - INFO - CROSSOVER IS OVER\n", + "2024-06-09 23:50:45,036 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:50:45,037 - root - INFO - Doing fitness calculating with individual {\"id\":\"5dfd07ae-6b8e-4da0-b5bc-b796561a6d18\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[19,792.0972147468201,-656.2726942221234]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.8513219009715824,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:45,038 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:45,988 - root - INFO - Training is complete\n", + "2024-06-09 23:50:46,172 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:46,173 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:46,321 - root - INFO - COMPONENTS 6.186980115632473 5.806005454099055\n", + "2024-06-09 23:50:46,576 - root - INFO - Fitness estimation took 1.54\n", + "2024-06-09 23:50:46,872 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:46,873 - root - INFO - Doing fitness calculating with individual {\"id\":\"77b7e91d-3c8c-4ac4-a3b6-ce6df2fd956b\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.9865394404766477,0.27797165579110483,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:46,874 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:49,384 - root - INFO - Training is complete\n", + "2024-06-09 23:50:49,775 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:49,777 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:50,131 - root - INFO - COMPONENTS 6.188726189260653 5.8981057732722135\n", + "2024-06-09 23:50:50,587 - root - INFO - Fitness estimation took 3.71\n", + "2024-06-09 23:50:50,951 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:50,952 - root - INFO - Doing fitness calculating with individual {\"id\":\"aeb70008-2f42-4579-8d99-efd18b992fdd\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:50,952 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:52,564 - root - INFO - Training is complete\n", + "2024-06-09 23:50:52,824 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:52,825 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:53,053 - root - INFO - COMPONENTS 6.169154511093149 5.917344732418264\n", + "2024-06-09 23:50:53,395 - root - INFO - Fitness estimation took 2.44\n", + "2024-06-09 23:50:53,713 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:53,714 - root - INFO - Doing fitness calculating with individual {\"id\":\"09d0dbd5-3e65-4df5-a020-3f51f74d9825\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[20,-243.7962682733213,377.65632437435534]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[5,0.2653884364897948,0.8513219009715824,0.7914820796771036]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:53,714 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:50:56,855 - root - INFO - Training is complete\n", + "2024-06-09 23:50:57,344 - root - INFO - Wow! all topics\n", + "2024-06-09 23:50:57,345 - root - INFO - Building dictionary\n", + "2024-06-09 23:50:57,820 - root - INFO - COMPONENTS 6.07978273175161 5.0187091750878166\n", + "2024-06-09 23:50:58,396 - root - INFO - Fitness estimation took 4.68\n", + "2024-06-09 23:50:58,820 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:50:58,821 - root - INFO - Doing fitness calculating with individual {\"id\":\"6ff56a84-161a-488a-970b-dc6052f21d18\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"DecorrelatorPhiRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"decorr\",\"distribution\":{\"low\":0.0,\"high\":100000.0}},{\"name\":\"decorr_2\",\"distribution\":{\"low\":0.0,\"high\":100000.0}}]},\"values\":[12,42463.83611995556,45061.758455273826]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":3,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:50:58,822 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:00,880 - root - INFO - Training is complete\n", + "2024-06-09 23:51:01,114 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:01,115 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:01,384 - root - INFO - COMPONENTS 2.1855207949599094 0.09994146701832968\n", + "2024-06-09 23:51:01,723 - root - INFO - Fitness estimation took 2.90\n", + "2024-06-09 23:51:02,022 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:02,023 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:51:02,024 - GA_algo - INFO - MUTATION IS OVER\n", + "2024-06-09 23:51:02,025 - GA_algo - INFO - Population len 11. Best params so far: pipeline=Pipeline(stages=[Stage(stage_type=StageType(name='SparseThetaRegularizer', params=[Param(name='n', distribution=IntRangeDistribution(low=1, high=30)), Param(name='SparsePhi', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0)), Param(name='SparseTheta', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0))]), values=[12, 862.6766687279264, 135.15287388864226])], required_params=Stage(stage_type=StageType(name='General', params=[Param(name='basic_topics_count', distribution=IntRangeDistribution(low=0, high=5)), Param(name='ext_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_elem_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_mutation_selector', distribution=FloatRangeDistribution(low=0.0, high=1.0))]), values=[0, 0.6065560125611166, 0.6935414883927496, 0.4825868764489578])), with fitness: 12.126965949662853.ITERATION TIME: 81.78789806365967DATASET __noname__.TOPICS NUM 25.RUN ID ee461a46-d514-43d0-952a-8b6c87bc1818.\n", + "2024-06-09 23:51:02,025 - root - INFO - Sending a best individual to be logged\n", + "2024-06-09 23:51:02,026 - root - INFO - Doing fitness calculating with individual {\"id\":\"5c2c8a77-5695-49f1-afc8-978c7264d5e9\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":{\"avg_coherence_score\":12.126965949662853,\"perplexityScore\":1367.0140380859375,\"backgroundTokensRatioScore\":0.05860655754804611,\"contrast\":0.0,\"purity\":0.0,\"kernelSize\":0.0,\"npmi_50_list\":null,\"npmi_50\":null,\"sparsity_phi\":0.0,\"sparsity_theta\":0.0,\"topic_significance_uni\":null,\"topic_significance_vacuous\":null,\"topic_significance_back\":null,\"switchP_list\":[NaN],\"switchP\":NaN,\"all_topics\":true,\"coherence_10_list\":[6.847273399192251,6.730724307314206,6.81015328161727,6.781480270718103,6.77694276559601,6.415694418173986,6.5402244804936425,6.782087644950563,6.701378569528667,6.856104842127825,6.715258904023474,6.906832410962406,6.805157772835139,6.784559318540944,6.71502212100932,6.917367857924914,6.698414702271158,6.991365593236741,6.723793753535029,6.907165820793221,6.855182938882594,6.705875024615536,6.736505993320824,6.436080993913767,6.685136164271975],\"coherence_10\":6.753031333993983,\"coherence_15_list\":[6.533259130184876,6.7434837491616255,6.676293077333751,6.622572816911698,6.634785696596075,6.524346738566347,6.807546066213145,6.815954094691511,6.616734862340504,6.806680003129368,6.7020103275216725,6.761203755026397,6.717342134701922,6.8652863809880085,6.50350987427352,6.7755456749933485,6.60972623815657,6.706803361581337,6.70538407883765,6.668008457557744,6.787711817480435,6.382209451443663,6.501393967308762,6.636975246871754,6.661356405379554],\"coherence_15\":6.67064493629005,\"coherence_20_list\":[6.543529778298098,6.659106257405972,6.55089693627856,6.601624053428274,6.477956477788523,6.584763982393815,6.656955728438524,6.712728119404426,6.725730382236146,6.699997856014576,6.718095271814978,6.702235053167015,6.847602816557056,6.783694536761621,6.496320847180677,6.8217283570841225,6.573961657039192,6.615320972439311,6.640206956571775,6.635693031269098,6.601603508474884,6.564475729543362,6.402111263533532,6.540205951744872,6.718571003168364],\"coherence_20\":6.635004661121472,\"coherence_25_list\":[6.4562658078034,6.59966394892218,6.630403748877014,6.690951976281171,6.488971781028378,6.577738053891906,6.523056981418214,6.723446755987442,6.718751309089274,6.5988511561993475,6.653573921873519,6.449681069821281,6.749235806281429,6.670130443377854,6.515019948150179,6.644008902225608,6.548021815408342,6.6152028000627165,6.50265717472447,6.585544502416424,6.5788085660430635,6.556676378307134,6.432315960631782,6.482272836867887,6.570576649251297],\"coherence_25\":6.582473131797652,\"coherence_30_list\":[6.498301850613089,6.522535683163357,6.49412486825226,6.572057095606508,6.4021018511757735,6.46322155791618,6.416418018786766,6.612127580417481,6.660997116306298,6.538956654187582,6.5562471519261605,6.430528212033041,6.465225422306231,6.466394285190932,6.441010902849499,6.589092563683,6.598103637604237,6.554074123829485,6.521299828945756,6.4539040677744,6.555482680895484,6.557706911577103,6.423998047441563,6.473138026882254,6.397376493040208],\"coherence_30\":6.506576985296187,\"coherence_35_list\":[6.403993328955538,6.462154149778253,6.440989520026369,6.4165717176204735,6.344841496274747,6.370768144675219,6.324671198303996,6.551281980225318,6.444174891534814,6.417394427334757,6.437859139213485,6.324413395987504,6.374993912044886,6.452615949237499,6.391256217156041,6.5181892514292326,6.419554682954688,6.51480769332043,6.4332619550790024,6.392868815504892,6.450582928822726,6.408463110518769,6.220838899490337,6.448118184151123,6.308714264986353],\"coherence_35\":6.410935170185058,\"coherence_40_list\":[6.30776544475684,6.440888689958534,6.393979992768134,6.297851305062039,6.322423057973425,6.239924453458568,6.3006782655132785,6.4747793056016185,6.3901285235578875,6.431380765162843,6.387165109423467,6.2123813395574,6.338190936249873,6.286209005533212,6.344914954513021,6.428270985096164,6.358408527484597,6.447132442119591,6.364551711901957,6.3073312319138894,6.1900493234735325,6.248089748961348,6.175713956500994,6.387114894051671,6.20572081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+ "2024-06-09 23:51:02,027 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:02,632 - root - INFO - Training is complete\n", + "2024-06-09 23:51:02,774 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:02,775 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:02,879 - root - INFO - COMPONENTS 6.180834003352823 5.94613194631003\n", + "2024-06-09 23:51:03,098 - root - INFO - Fitness estimation took 1.07\n", + "2024-06-09 23:51:03,323 - root - INFO - Logging params and artifacts to mlflow\n", + "2024-06-09 23:51:03,323 - root - INFO - Created experiment_0\n", + "2024-06-09 23:51:03,341 - root - INFO - Experiment exists, omitting creation\n", + "2024-06-09 23:51:03,342 - root - INFO - Experiment run name: fitness-__noname__-5a1db301-36f5-40fb-ae5f-1227ccf5af3b_tmp_3\n", + "2024-06-09 23:51:03,415 - root - DEBUG - Params dict: {'0_General_basic_topics_count': 0, '0_General_ext_mutation_prob': 0.6065560125611166, '0_General_ext_elem_mutation_prob': 0.6935414883927496, '0_General_ext_mutation_selector': 0.4825868764489578, '1_SparseThetaRegularizer_n': 12, '1_SparseThetaRegularizer_SparsePhi': 862.6766687279264, '1_SparseThetaRegularizer_SparseTheta': 135.15287388864226}\n", + "2024-06-09 23:51:03,904 - root - INFO - Logged params and artifacts to mlflow\n", + "2024-06-09 23:51:03,965 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:03,966 - GA_algo - INFO - ENTERING GENERATION 4\n", + "2024-06-09 23:51:03,967 - GA_algo - INFO - PAIRS ARE CREATED\n", + "2024-06-09 23:51:03,974 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:51:03,976 - root - INFO - Doing fitness calculating with individual {\"id\":\"c4713ed1-2cce-46d1-81a4-6655aeb0e1d8\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[5,0.2653884364897948,0.8513219009715824,0.7914820796771036]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:03,976 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:05,463 - root - INFO - Training is complete\n", + "2024-06-09 23:51:05,734 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:05,735 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:05,972 - root - INFO - COMPONENTS 6.169403230192717 5.885853870558686\n", + "2024-06-09 23:51:06,312 - root - INFO - Fitness estimation took 2.34\n", + "2024-06-09 23:51:06,656 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:06,657 - root - INFO - Doing fitness calculating with individual {\"id\":\"6b7adb5a-cd6d-459d-a019-8f293cf9830f\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[20,-243.7962682733213,377.65632437435534]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:06,658 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:08,833 - root - INFO - Training is complete\n", + "2024-06-09 23:51:09,164 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:09,165 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:09,482 - root - INFO - COMPONENTS 6.1092472151694315 5.225455414322394\n", + "2024-06-09 23:51:09,889 - root - INFO - Fitness estimation took 3.23\n", + "2024-06-09 23:51:10,239 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:10,240 - root - INFO - Doing fitness calculating with individual {\"id\":\"0e90ebcb-e863-40fe-a69e-90edf0b543ef\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:10,241 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:11,284 - root - INFO - Training is complete\n", + "2024-06-09 23:51:11,473 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:11,474 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:11,632 - root - INFO - COMPONENTS 6.182406147784217 5.885853870558685\n", + "2024-06-09 23:51:11,900 - root - INFO - Fitness estimation took 1.66\n", + "2024-06-09 23:51:12,196 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:12,197 - root - INFO - Doing fitness calculating with individual {\"id\":\"622b9d4a-6cc8-49ac-84da-64a402766367\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:12,198 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:13,956 - root - INFO - Training is complete\n", + "2024-06-09 23:51:14,230 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:14,231 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:14,477 - root - INFO - COMPONENTS 6.185224270770298 5.852301534971088\n", + "2024-06-09 23:51:14,830 - root - INFO - Fitness estimation took 2.63\n", + "2024-06-09 23:51:15,153 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:15,154 - root - INFO - Doing fitness calculating with individual {\"id\":\"dd06d17a-9d55-48cb-bc8d-ac0d5175a911\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[19,792.0972147468201,-656.2726942221234]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:15,155 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:16,665 - root - INFO - Training is complete\n", + "2024-06-09 23:51:16,912 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:16,913 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:17,129 - root - INFO - COMPONENTS 6.162223131789546 5.541142694281492\n", + "2024-06-09 23:51:17,456 - root - INFO - Fitness estimation took 2.30\n", + "2024-06-09 23:51:17,777 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:17,778 - root - INFO - Doing fitness calculating with individual {\"id\":\"28c539eb-285d-44cc-a769-897dfd73f532\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.9865394404766477,0.6935414883927496,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:17,779 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:20,286 - root - INFO - Training is complete\n", + "2024-06-09 23:51:20,663 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:20,664 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:21,015 - root - INFO - COMPONENTS 6.189495747626496 5.917344732418264\n", + "2024-06-09 23:51:21,468 - root - INFO - Fitness estimation took 3.69\n", + "2024-06-09 23:51:21,837 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:21,838 - root - INFO - Doing fitness calculating with individual {\"id\":\"6fbd2293-e2e1-4306-8f7e-ed4c6ba9e049\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.27797165579110483,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:21,839 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:22,450 - root - INFO - Training is complete\n", + "2024-06-09 23:51:22,589 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:22,590 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:22,695 - root - INFO - COMPONENTS 6.180834003352823 5.94613194631003\n", + "2024-06-09 23:51:22,912 - root - INFO - Fitness estimation took 1.07\n", + "2024-06-09 23:51:23,191 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:23,192 - root - INFO - Doing fitness calculating with individual {\"id\":\"f6256d00-196e-4498-a878-f3fc8cf239c7\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:23,193 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:24,827 - root - INFO - Training is complete\n", + "2024-06-09 23:51:25,098 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:25,099 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:25,325 - root - INFO - COMPONENTS 6.187896925587603 5.917344732418264\n", + "2024-06-09 23:51:25,658 - root - INFO - Fitness estimation took 2.47\n", + "2024-06-09 23:51:25,983 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:25,985 - root - INFO - Doing fitness calculating with individual {\"id\":\"2e7585c0-8e5d-4781-9984-6d11dbcfce5c\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:25,985 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:27,168 - root - INFO - Training is complete\n", + "2024-06-09 23:51:27,373 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:27,374 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:27,554 - root - INFO - COMPONENTS 6.181608210338693 5.8523015349710885\n", + "2024-06-09 23:51:27,835 - root - INFO - Fitness estimation took 1.85\n", + "2024-06-09 23:51:28,136 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:28,137 - root - INFO - Doing fitness calculating with individual {\"id\":\"7a91d258-4bb9-419d-9f05-c9122a9f54a5\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:28,137 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:29,752 - root - INFO - Training is complete\n", + "2024-06-09 23:51:30,011 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:30,012 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:30,243 - root - INFO - COMPONENTS 6.169154511093149 5.917344732418264\n", + "2024-06-09 23:51:30,580 - root - INFO - Fitness estimation took 2.44\n", + "2024-06-09 23:51:30,903 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:30,904 - root - INFO - Doing fitness calculating with individual {\"id\":\"ca684d36-655a-4ba0-96b2-9ba0a3cb1cf3\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:30,905 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:33,124 - root - INFO - Training is complete\n", + "2024-06-09 23:51:33,451 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:33,452 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:33,754 - root - INFO - COMPONENTS 6.155609032546838 5.6832171011647885\n", + "2024-06-09 23:51:34,163 - root - INFO - Fitness estimation took 3.26\n", + "2024-06-09 23:51:34,511 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:34,512 - root - INFO - Doing fitness calculating with individual {\"id\":\"2055afd3-19d4-4bc5-b3ba-a596108425cd\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:34,513 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:38,551 - root - INFO - Training is complete\n", + "2024-06-09 23:51:39,139 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:39,140 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:39,703 - root - INFO - COMPONENTS 6.181756063843047 5.8736574800087595\n", + "2024-06-09 23:51:40,362 - root - INFO - Fitness estimation took 5.85\n", + "2024-06-09 23:51:40,800 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:40,801 - root - INFO - Doing fitness calculating with individual {\"id\":\"20ca9165-d249-403a-8ed7-e413c5d1e37d\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.20382144321324902,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:40,802 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:41,979 - root - INFO - Training is complete\n", + "2024-06-09 23:51:42,185 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:42,186 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:42,360 - root - INFO - COMPONENTS 6.181608210338693 5.8523015349710885\n", + "2024-06-09 23:51:42,641 - root - INFO - Fitness estimation took 1.84\n", + "2024-06-09 23:51:42,941 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:42,942 - root - INFO - Doing fitness calculating with individual {\"id\":\"9f43c933-2c40-4c1e-88ee-5a0a952c9268\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:42,943 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:45,767 - root - INFO - Training is complete\n", + "2024-06-09 23:51:46,201 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:46,202 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:46,594 - root - INFO - COMPONENTS 6.1814880221685735 5.8981057732722135\n", + "2024-06-09 23:51:47,088 - root - INFO - Fitness estimation took 4.15\n", + "2024-06-09 23:51:47,475 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:47,476 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:51:47,477 - GA_algo - INFO - size of the new generation is 14\n", + "2024-06-09 23:51:47,478 - GA_algo - INFO - CROSSOVER IS OVER\n", + "2024-06-09 23:51:47,775 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:51:47,777 - root - INFO - Doing fitness calculating with individual {\"id\":\"475e5af1-f72d-45c2-9f66-391d2697bd25\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[27,-876.0861302782879,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.9865394404766477,0.6935414883927496,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:47,777 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:50,903 - root - INFO - Training is complete\n", + "2024-06-09 23:51:50,994 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:51,027 - root - INFO - COMPONENTS 0.0 0\n", + "2024-06-09 23:51:51,047 - root - INFO - Fitness estimation took 3.27\n", + "2024-06-09 23:51:51,227 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:51,228 - root - INFO - Doing fitness calculating with individual {\"id\":\"ab8ffd9e-90f6-42df-9612-9f12d4893ad7\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.9865394404766477,0.27797165579110483,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:51,228 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:53,737 - root - INFO - Training is complete\n", + "2024-06-09 23:51:54,114 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:54,115 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:54,469 - root - INFO - COMPONENTS 6.182734738627638 5.8981057732722135\n", + "2024-06-09 23:51:54,921 - root - INFO - Fitness estimation took 3.69\n", + "2024-06-09 23:51:55,283 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:55,285 - root - INFO - Doing fitness calculating with individual {\"id\":\"376f2e1a-679f-4d77-883d-f60a98cc57f0\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,-368.1747539292046,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:55,285 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:56,856 - root - INFO - Training is complete\n", + "2024-06-09 23:51:57,049 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:57,183 - root - INFO - COMPONENTS 0.0 0\n", + "2024-06-09 23:51:57,311 - root - INFO - Fitness estimation took 2.03\n", + "2024-06-09 23:51:57,510 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:57,511 - root - INFO - Doing fitness calculating with individual {\"id\":\"4534d71b-e392-476f-8092-55552f2181a0\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,127.81269507937509,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:57,512 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:51:58,896 - root - INFO - Training is complete\n", + "2024-06-09 23:51:59,121 - root - INFO - Wow! all topics\n", + "2024-06-09 23:51:59,122 - root - INFO - Building dictionary\n", + "2024-06-09 23:51:59,314 - root - INFO - COMPONENTS 6.180268089278663 5.917344732418264\n", + "2024-06-09 23:51:59,616 - root - INFO - Fitness estimation took 2.10\n", + "2024-06-09 23:51:59,925 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:51:59,926 - root - INFO - Doing fitness calculating with individual {\"id\":\"a17da81e-c40b-40f9-b52c-6d76de8a0839\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.053890396724473266,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:51:59,926 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:02,751 - root - INFO - Training is complete\n", + "2024-06-09 23:52:03,182 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:03,183 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:03,592 - root - INFO - COMPONENTS 6.1814880221685735 5.8981057732722135\n", + "2024-06-09 23:52:04,103 - root - INFO - Fitness estimation took 4.18\n", + "2024-06-09 23:52:04,488 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:04,488 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:52:04,489 - GA_algo - INFO - MUTATION IS OVER\n", + "2024-06-09 23:52:04,490 - GA_algo - INFO - Population len 11. Best params so far: pipeline=Pipeline(stages=[Stage(stage_type=StageType(name='SparseThetaRegularizer', params=[Param(name='n', distribution=IntRangeDistribution(low=1, high=30)), Param(name='SparsePhi', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0)), Param(name='SparseTheta', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0))]), values=[12, 862.6766687279264, 135.15287388864226])], required_params=Stage(stage_type=StageType(name='General', params=[Param(name='basic_topics_count', distribution=IntRangeDistribution(low=0, high=5)), Param(name='ext_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_elem_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_mutation_selector', distribution=FloatRangeDistribution(low=0.0, high=1.0))]), values=[0, 0.6065560125611166, 0.6935414883927496, 0.4825868764489578])), with fitness: 12.126965949662853.ITERATION TIME: 60.524157762527466DATASET __noname__.TOPICS NUM 25.RUN ID ee461a46-d514-43d0-952a-8b6c87bc1818.\n", + "2024-06-09 23:52:04,491 - root - INFO - Sending a best individual to be logged\n", + "2024-06-09 23:52:04,492 - root - INFO - Doing fitness calculating with individual {\"id\":\"5c2c8a77-5695-49f1-afc8-978c7264d5e9\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":{\"avg_coherence_score\":12.126965949662853,\"perplexityScore\":1367.0140380859375,\"backgroundTokensRatioScore\":0.05860655754804611,\"contrast\":0.0,\"purity\":0.0,\"kernelSize\":0.0,\"npmi_50_list\":null,\"npmi_50\":null,\"sparsity_phi\":0.0,\"sparsity_theta\":0.0,\"topic_significance_uni\":null,\"topic_significance_vacuous\":null,\"topic_significance_back\":null,\"switchP_list\":[NaN],\"switchP\":NaN,\"all_topics\":true,\"coherence_10_list\":[6.847273399192251,6.730724307314206,6.81015328161727,6.781480270718103,6.77694276559601,6.415694418173986,6.5402244804936425,6.782087644950563,6.701378569528667,6.856104842127825,6.715258904023474,6.906832410962406,6.805157772835139,6.784559318540944,6.71502212100932,6.917367857924914,6.698414702271158,6.991365593236741,6.723793753535029,6.907165820793221,6.855182938882594,6.705875024615536,6.736505993320824,6.436080993913767,6.685136164271975],\"coherence_10\":6.753031333993983,\"coherence_15_list\":[6.533259130184876,6.7434837491616255,6.676293077333751,6.622572816911698,6.634785696596075,6.524346738566347,6.807546066213145,6.815954094691511,6.616734862340504,6.806680003129368,6.7020103275216725,6.761203755026397,6.717342134701922,6.8652863809880085,6.50350987427352,6.7755456749933485,6.60972623815657,6.706803361581337,6.70538407883765,6.668008457557744,6.787711817480435,6.382209451443663,6.501393967308762,6.636975246871754,6.661356405379554],\"coherence_15\":6.67064493629005,\"coherence_20_list\":[6.543529778298098,6.659106257405972,6.55089693627856,6.601624053428274,6.477956477788523,6.584763982393815,6.656955728438524,6.712728119404426,6.725730382236146,6.699997856014576,6.718095271814978,6.702235053167015,6.847602816557056,6.783694536761621,6.496320847180677,6.8217283570841225,6.573961657039192,6.615320972439311,6.640206956571775,6.635693031269098,6.601603508474884,6.564475729543362,6.402111263533532,6.540205951744872,6.718571003168364],\"coherence_20\":6.635004661121472,\"coherence_25_list\":[6.4562658078034,6.59966394892218,6.630403748877014,6.690951976281171,6.488971781028378,6.577738053891906,6.523056981418214,6.723446755987442,6.718751309089274,6.5988511561993475,6.653573921873519,6.449681069821281,6.749235806281429,6.670130443377854,6.515019948150179,6.644008902225608,6.548021815408342,6.6152028000627165,6.50265717472447,6.585544502416424,6.5788085660430635,6.556676378307134,6.432315960631782,6.482272836867887,6.570576649251297],\"coherence_25\":6.582473131797652,\"coherence_30_list\":[6.498301850613089,6.522535683163357,6.49412486825226,6.572057095606508,6.4021018511757735,6.46322155791618,6.416418018786766,6.612127580417481,6.660997116306298,6.538956654187582,6.5562471519261605,6.430528212033041,6.465225422306231,6.466394285190932,6.441010902849499,6.589092563683,6.598103637604237,6.554074123829485,6.521299828945756,6.4539040677744,6.555482680895484,6.557706911577103,6.423998047441563,6.473138026882254,6.397376493040208],\"coherence_30\":6.506576985296187,\"coherence_35_list\":[6.403993328955538,6.462154149778253,6.440989520026369,6.4165717176204735,6.344841496274747,6.370768144675219,6.324671198303996,6.551281980225318,6.444174891534814,6.417394427334757,6.437859139213485,6.324413395987504,6.374993912044886,6.452615949237499,6.391256217156041,6.5181892514292326,6.419554682954688,6.51480769332043,6.4332619550790024,6.392868815504892,6.450582928822726,6.408463110518769,6.220838899490337,6.448118184151123,6.308714264986353],\"coherence_35\":6.410935170185058,\"coherence_40_list\":[6.30776544475684,6.440888689958534,6.393979992768134,6.297851305062039,6.322423057973425,6.239924453458568,6.3006782655132785,6.4747793056016185,6.3901285235578875,6.431380765162843,6.387165109423467,6.2123813395574,6.338190936249873,6.286209005533212,6.344914954513021,6.428270985096164,6.358408527484597,6.447132442119591,6.364551711901957,6.3073312319138894,6.1900493234735325,6.248089748961348,6.175713956500994,6.387114894051671,6.205720811567557],\"coherence_40\":6.331241791286456,\"coherence_45_list\":[6.196164221994946,6.351691112650757,6.3876871616475634,6.2169367259764,6.2700687095415955,6.154446551697229,6.17751286550516,6.497909083831898,6.350876703135634,6.353290419225084,6.273368257422746,6.10877835770136,6.125628963460158,6.163246233493589,6.285113911098988,6.387130315208957,6.27931548552275,6.413741896156556,6.239117383936755,6.292372700874718,6.092104690588711,6.243802338228963,6.118583431499146,6.301566496512477,6.146092099903227],\"coherence_45\":6.257061844672615,\"coherence_50_list\":[6.148699935315383,6.326911028321904,6.239947269495553,6.184194116344167,6.213987750895649,6.154614045231385,6.101080248667447,6.408587979920304,6.254104246981741,6.249013718990919,6.265822702728159,6.0037499668126015,6.018770607969764,6.1650329870269305,6.180272942662255,6.25422435765407,6.166204569308145,6.334086157926717,6.170494242529895,6.236511466949228,6.050193270336161,6.1273842321012815,5.94613194631003,6.209544392561376,6.111285900779486],\"coherence_50\":6.180834003352823,\"coherence_55_list\":[6.153647478055628,6.28603684260796,6.212023155321504,6.1382169485543345,6.074421697343837,6.104739726572959,6.051968223883241,6.169135553843967,6.195168094416744,6.242748775556229,6.199417846435927,5.9910717059339165,6.025975591178977,6.014461955408583,6.089510694517783,6.102852534309653,6.113577271330549,6.245489116366203,6.099461673251516,6.111546243466477,5.994337079709307,6.072900822653464,5.803431514985174,6.111547412573434,6.055213608917615],\"coherence_55\":6.1063560626878,\"npmi_15\":null,\"npmi_25\":null},\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":4,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:04,493 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:05,096 - root - INFO - Training is complete\n", + "2024-06-09 23:52:05,236 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:05,237 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:05,340 - root - INFO - COMPONENTS 6.180834003352823 5.94613194631003\n", + "2024-06-09 23:52:05,559 - root - INFO - Fitness estimation took 1.07\n", + "2024-06-09 23:52:05,779 - root - INFO - Logging params and artifacts to mlflow\n", + "2024-06-09 23:52:05,779 - root - INFO - Created experiment_0\n", + "2024-06-09 23:52:05,802 - root - INFO - Experiment exists, omitting creation\n", + "2024-06-09 23:52:05,803 - root - INFO - Experiment run name: fitness-__noname__-56d20661-f497-4f1f-8c36-451aa3a69c6d_tmp_4\n", + "2024-06-09 23:52:05,876 - root - DEBUG - Params dict: {'0_General_basic_topics_count': 0, '0_General_ext_mutation_prob': 0.6065560125611166, '0_General_ext_elem_mutation_prob': 0.6935414883927496, '0_General_ext_mutation_selector': 0.4825868764489578, '1_SparseThetaRegularizer_n': 12, '1_SparseThetaRegularizer_SparsePhi': 862.6766687279264, '1_SparseThetaRegularizer_SparseTheta': 135.15287388864226}\n", + "2024-06-09 23:52:06,383 - root - INFO - Logged params and artifacts to mlflow\n", + "2024-06-09 23:52:06,439 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:06,439 - GA_algo - INFO - ENTERING GENERATION 5\n", + "2024-06-09 23:52:06,440 - GA_algo - INFO - PAIRS ARE CREATED\n", + "2024-06-09 23:52:06,447 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:52:06,448 - root - INFO - Doing fitness calculating with individual {\"id\":\"300cf71a-856f-4dc1-8f66-691170088185\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.27797165579110483,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":5,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:06,449 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:07,633 - root - INFO - Training is complete\n", + "2024-06-09 23:52:07,847 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:07,848 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:08,019 - root - INFO - COMPONENTS 6.181608210338693 5.8523015349710885\n", + "2024-06-09 23:52:08,306 - root - INFO - Fitness estimation took 1.86\n", + "2024-06-09 23:52:08,618 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:08,619 - root - INFO - Doing fitness calculating with individual {\"id\":\"fcc2a1e6-ed9c-4dda-95fc-1c05d48fc203\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.27797165579110483,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":5,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:08,620 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:09,810 - root - INFO - Training is complete\n", + "2024-06-09 23:52:10,015 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:10,016 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:10,188 - root - INFO - COMPONENTS 6.181608210338693 5.8523015349710885\n", + "2024-06-09 23:52:10,470 - root - INFO - Fitness estimation took 1.85\n", + "2024-06-09 23:52:10,776 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:10,777 - root - INFO - Doing fitness calculating with individual {\"id\":\"7003c7ef-ceca-47e1-920a-185fdd48cb45\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":5,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:10,778 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:12,814 - root - INFO - Training is complete\n", + "2024-06-09 23:52:13,136 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:13,137 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:13,428 - root - INFO - COMPONENTS 6.177241647042988 5.885853870558686\n", + "2024-06-09 23:52:13,822 - root - INFO - Fitness estimation took 3.04\n", + "2024-06-09 23:52:14,166 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:14,167 - root - INFO - Doing fitness calculating with individual {\"id\":\"95fbcedf-adc5-434a-96e6-cf5ba6e973db\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":5,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:14,167 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:16,572 - root - INFO - Training is complete\n", + "2024-06-09 23:52:16,924 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:16,925 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:17,249 - root - INFO - COMPONENTS 6.153941467392035 5.65767683474334\n", + "2024-06-09 23:52:17,678 - root - INFO - Fitness estimation took 3.51\n", + "2024-06-09 23:52:18,033 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:18,034 - root - INFO - Doing fitness calculating with individual {\"id\":\"afff9e76-80e3-4c7f-b205-c3471ff7214e\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.053890396724473266,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":5,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:18,035 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:21,457 - root - INFO - Training is complete\n", + "2024-06-09 23:52:21,985 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:21,986 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:22,503 - root - INFO - COMPONENTS 6.188957533238761 5.917344732418264\n", + "2024-06-09 23:52:23,108 - root - INFO - Fitness estimation took 5.07\n", + "2024-06-09 23:52:23,546 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:23,547 - root - INFO - Doing fitness calculating with individual {\"id\":\"8cd61bdb-9699-4300-a340-afd0a7f97c98\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.6065560125611166,0.6935414883927496,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":5,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:23,548 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:25,482 - root - INFO - Training is complete\n", + "2024-06-09 23:52:25,784 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:25,785 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:26,058 - root - INFO - COMPONENTS 6.187430583347987 5.8981057732722135\n", + "2024-06-09 23:52:26,439 - root - INFO - Fitness estimation took 2.89\n", + "2024-06-09 23:52:26,785 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:26,786 - root - INFO - Doing fitness calculating with individual {\"id\":\"3b3e13e2-6d23-44ab-8e8e-8815f711929b\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.9865394404766477,0.27797165579110483,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":5,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:26,786 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:27,969 - root - INFO - Training is complete\n", + "2024-06-09 23:52:28,175 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:28,176 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:28,350 - root - INFO - COMPONENTS 6.181608210338693 5.8523015349710885\n", + "2024-06-09 23:52:28,635 - root - INFO - Fitness estimation took 1.85\n", + "2024-06-09 23:52:28,938 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:28,939 - root - INFO - Doing fitness calculating with individual {\"id\":\"645f4674-1f1a-4f64-bab9-187cb09f099f\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.9865394404766477,0.27797165579110483,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":5,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:28,940 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:31,203 - root - INFO - Training is complete\n", + "2024-06-09 23:52:31,535 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:31,536 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:31,846 - root - INFO - COMPONENTS 6.184427337172455 5.917344732418264\n", + "2024-06-09 23:52:32,262 - root - INFO - Fitness estimation took 3.32\n", + "2024-06-09 23:52:32,614 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:32,616 - root - INFO - Doing fitness calculating with individual {\"id\":\"5c5cf71a-a1d5-4f8b-b71e-0f3ea049c627\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":5,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:32,616 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:35,106 - root - INFO - Training is complete\n", + "2024-06-09 23:52:35,466 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:35,467 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:35,803 - root - INFO - COMPONENTS 6.191277653428191 5.917344732418264\n", + "2024-06-09 23:52:36,247 - root - INFO - Fitness estimation took 3.63\n", + "2024-06-09 23:52:36,598 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:36,598 - root - INFO - Doing fitness calculating with individual {\"id\":\"f38d0eb9-32da-4d59-bd91-dcfe0490cc34\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":5,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:36,599 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:37,638 - root - INFO - Training is complete\n", + "2024-06-09 23:52:37,834 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:37,835 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:37,991 - root - INFO - COMPONENTS 6.182406147784217 5.885853870558685\n", + "2024-06-09 23:52:38,258 - root - INFO - Fitness estimation took 1.66\n", + "2024-06-09 23:52:38,565 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:38,566 - root - INFO - Doing fitness calculating with individual {\"id\":\"4505efa6-f912-423f-85d3-71a76b36ce14\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":5,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:38,567 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:40,346 - root - INFO - Training is complete\n", + "2024-06-09 23:52:40,630 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:40,631 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:40,885 - root - INFO - COMPONENTS 6.185224270770298 5.852301534971088\n", + "2024-06-09 23:52:41,245 - root - INFO - Fitness estimation took 2.68\n", + "2024-06-09 23:52:41,567 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:41,568 - root - INFO - Doing fitness calculating with individual {\"id\":\"cd879ea9-84ed-4b7a-872c-671d9fba742e\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":5,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:41,569 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:43,764 - root - INFO - Training is complete\n", + "2024-06-09 23:52:44,093 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:44,094 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:44,406 - root - INFO - COMPONENTS 6.157197321178891 5.6873829945114815\n", + "2024-06-09 23:52:44,820 - root - INFO - Fitness estimation took 3.25\n", + "2024-06-09 23:52:45,170 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:45,170 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:52:45,171 - GA_algo - INFO - size of the new generation is 12\n", + "2024-06-09 23:52:45,172 - GA_algo - INFO - CROSSOVER IS OVER\n", + "2024-06-09 23:52:45,464 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:52:45,465 - root - INFO - Doing fitness calculating with individual {\"id\":\"d6ba78d6-aac9-44a0-becb-11d8d5329a00\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[27,862.6766687279264,171.93081573591508]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.27797165579110483,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":5,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:45,465 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:46,791 - root - INFO - Training is complete\n", + "2024-06-09 23:52:47,014 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:47,015 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:47,206 - root - INFO - COMPONENTS 6.179985289637732 5.8523015349710885\n", + "2024-06-09 23:52:47,504 - root - INFO - Fitness estimation took 2.04\n", + "2024-06-09 23:52:47,803 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:47,804 - root - INFO - Doing fitness calculating with individual {\"id\":\"1a766a97-da12-4be4-9180-1ae1a0f4bb63\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":5,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:47,805 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:50,266 - root - INFO - Training is complete\n", + "2024-06-09 23:52:50,632 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:50,633 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:50,967 - root - INFO - COMPONENTS 6.153218461618177 5.708420059574213\n", + "2024-06-09 23:52:51,412 - root - INFO - Fitness estimation took 3.61\n", + "2024-06-09 23:52:51,771 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:51,772 - root - INFO - Doing fitness calculating with individual {\"id\":\"2deb2e14-9d90-43be-9bc4-1718fbb55c43\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":5,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:51,773 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:52,804 - root - INFO - Training is complete\n", + "2024-06-09 23:52:52,995 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:52,996 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:53,150 - root - INFO - COMPONENTS 6.182406147784217 5.885853870558685\n", + "2024-06-09 23:52:53,416 - root - INFO - Fitness estimation took 1.64\n", + "2024-06-09 23:52:53,710 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:53,711 - root - INFO - Doing fitness calculating with individual {\"id\":\"3eb0ad39-6a0f-434a-8251-9fc7404a5864\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,-137.28976639465884]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.9865394404766477,0.27797165579110483,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":5,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:53,712 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:55,798 - root - INFO - Training is complete\n", + "2024-06-09 23:52:56,012 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:56,164 - root - INFO - COMPONENTS 0.0 0\n", + "2024-06-09 23:52:56,308 - root - INFO - Fitness estimation took 2.60\n", + "2024-06-09 23:52:56,508 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:56,509 - root - INFO - Doing fitness calculating with individual {\"id\":\"03d3160d-ca6f-47de-a088-21e8ea637ba7\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,127.81269507937509,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":5,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:52:56,510 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:57,588 - root - INFO - Training is complete\n", + "2024-06-09 23:52:57,782 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:57,783 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:57,944 - root - INFO - COMPONENTS 6.1828272353185305 5.885853870558686\n", + "2024-06-09 23:52:58,215 - root - INFO - Fitness estimation took 1.71\n", + "2024-06-09 23:52:58,515 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:52:58,516 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:52:58,517 - GA_algo - INFO - MUTATION IS OVER\n", + "2024-06-09 23:52:58,518 - GA_algo - INFO - Population len 11. Best params so far: pipeline=Pipeline(stages=[Stage(stage_type=StageType(name='SparseThetaRegularizer', params=[Param(name='n', distribution=IntRangeDistribution(low=1, high=30)), Param(name='SparsePhi', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0)), Param(name='SparseTheta', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0))]), values=[12, 862.6766687279264, 135.15287388864226])], required_params=Stage(stage_type=StageType(name='General', params=[Param(name='basic_topics_count', distribution=IntRangeDistribution(low=0, high=5)), Param(name='ext_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_elem_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_mutation_selector', distribution=FloatRangeDistribution(low=0.0, high=1.0))]), values=[0, 0.6065560125611166, 0.6935414883927496, 0.4825868764489578])), with fitness: 12.126965949662853.ITERATION TIME: 52.078529834747314DATASET __noname__.TOPICS NUM 25.RUN ID ee461a46-d514-43d0-952a-8b6c87bc1818.\n", + "2024-06-09 23:52:58,518 - root - INFO - Sending a best individual to be logged\n", + "2024-06-09 23:52:58,520 - root - INFO - Doing fitness calculating with individual {\"id\":\"5c2c8a77-5695-49f1-afc8-978c7264d5e9\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":{\"avg_coherence_score\":12.126965949662853,\"perplexityScore\":1367.0140380859375,\"backgroundTokensRatioScore\":0.05860655754804611,\"contrast\":0.0,\"purity\":0.0,\"kernelSize\":0.0,\"npmi_50_list\":null,\"npmi_50\":null,\"sparsity_phi\":0.0,\"sparsity_theta\":0.0,\"topic_significance_uni\":null,\"topic_significance_vacuous\":null,\"topic_significance_back\":null,\"switchP_list\":[NaN],\"switchP\":NaN,\"all_topics\":true,\"coherence_10_list\":[6.847273399192251,6.730724307314206,6.81015328161727,6.781480270718103,6.77694276559601,6.415694418173986,6.5402244804936425,6.782087644950563,6.701378569528667,6.856104842127825,6.715258904023474,6.906832410962406,6.805157772835139,6.784559318540944,6.71502212100932,6.917367857924914,6.698414702271158,6.991365593236741,6.723793753535029,6.907165820793221,6.855182938882594,6.705875024615536,6.736505993320824,6.436080993913767,6.685136164271975],\"coherence_10\":6.753031333993983,\"coherence_15_list\":[6.533259130184876,6.7434837491616255,6.676293077333751,6.622572816911698,6.634785696596075,6.524346738566347,6.807546066213145,6.815954094691511,6.616734862340504,6.806680003129368,6.7020103275216725,6.761203755026397,6.717342134701922,6.8652863809880085,6.50350987427352,6.7755456749933485,6.60972623815657,6.706803361581337,6.70538407883765,6.668008457557744,6.787711817480435,6.382209451443663,6.501393967308762,6.636975246871754,6.661356405379554],\"coherence_15\":6.67064493629005,\"coherence_20_list\":[6.543529778298098,6.659106257405972,6.55089693627856,6.601624053428274,6.477956477788523,6.584763982393815,6.656955728438524,6.712728119404426,6.725730382236146,6.699997856014576,6.718095271814978,6.702235053167015,6.847602816557056,6.783694536761621,6.496320847180677,6.8217283570841225,6.573961657039192,6.615320972439311,6.640206956571775,6.635693031269098,6.601603508474884,6.564475729543362,6.402111263533532,6.540205951744872,6.718571003168364],\"coherence_20\":6.635004661121472,\"coherence_25_list\":[6.4562658078034,6.59966394892218,6.630403748877014,6.690951976281171,6.488971781028378,6.577738053891906,6.523056981418214,6.723446755987442,6.718751309089274,6.5988511561993475,6.653573921873519,6.449681069821281,6.749235806281429,6.670130443377854,6.515019948150179,6.644008902225608,6.548021815408342,6.6152028000627165,6.50265717472447,6.585544502416424,6.5788085660430635,6.556676378307134,6.432315960631782,6.482272836867887,6.570576649251297],\"coherence_25\":6.582473131797652,\"coherence_30_list\":[6.498301850613089,6.522535683163357,6.49412486825226,6.572057095606508,6.4021018511757735,6.46322155791618,6.416418018786766,6.612127580417481,6.660997116306298,6.538956654187582,6.5562471519261605,6.430528212033041,6.465225422306231,6.466394285190932,6.441010902849499,6.589092563683,6.598103637604237,6.554074123829485,6.521299828945756,6.4539040677744,6.555482680895484,6.557706911577103,6.423998047441563,6.473138026882254,6.397376493040208],\"coherence_30\":6.506576985296187,\"coherence_35_list\":[6.403993328955538,6.462154149778253,6.440989520026369,6.4165717176204735,6.344841496274747,6.370768144675219,6.324671198303996,6.551281980225318,6.444174891534814,6.417394427334757,6.437859139213485,6.324413395987504,6.374993912044886,6.452615949237499,6.391256217156041,6.5181892514292326,6.419554682954688,6.51480769332043,6.4332619550790024,6.392868815504892,6.450582928822726,6.408463110518769,6.220838899490337,6.448118184151123,6.308714264986353],\"coherence_35\":6.410935170185058,\"coherence_40_list\":[6.30776544475684,6.440888689958534,6.393979992768134,6.297851305062039,6.322423057973425,6.239924453458568,6.3006782655132785,6.4747793056016185,6.3901285235578875,6.431380765162843,6.387165109423467,6.2123813395574,6.338190936249873,6.286209005533212,6.344914954513021,6.428270985096164,6.358408527484597,6.447132442119591,6.364551711901957,6.3073312319138894,6.1900493234735325,6.248089748961348,6.175713956500994,6.387114894051671,6.20572081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+ "2024-06-09 23:52:58,521 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:52:59,121 - root - INFO - Training is complete\n", + "2024-06-09 23:52:59,260 - root - INFO - Wow! all topics\n", + "2024-06-09 23:52:59,260 - root - INFO - Building dictionary\n", + "2024-06-09 23:52:59,363 - root - INFO - COMPONENTS 6.180834003352823 5.94613194631003\n", + "2024-06-09 23:52:59,578 - root - INFO - Fitness estimation took 1.06\n", + "2024-06-09 23:52:59,797 - root - INFO - Logging params and artifacts to mlflow\n", + "2024-06-09 23:52:59,798 - root - INFO - Created experiment_0\n", + "2024-06-09 23:52:59,814 - root - INFO - Experiment exists, omitting creation\n", + "2024-06-09 23:52:59,814 - root - INFO - Experiment run name: fitness-__noname__-4528d9da-6141-4373-b66f-281d800fc13b_tmp_5\n", + "2024-06-09 23:52:59,888 - root - DEBUG - Params dict: {'0_General_basic_topics_count': 0, '0_General_ext_mutation_prob': 0.6065560125611166, '0_General_ext_elem_mutation_prob': 0.6935414883927496, '0_General_ext_mutation_selector': 0.4825868764489578, '1_SparseThetaRegularizer_n': 12, '1_SparseThetaRegularizer_SparsePhi': 862.6766687279264, '1_SparseThetaRegularizer_SparseTheta': 135.15287388864226}\n", + "2024-06-09 23:53:00,436 - root - INFO - Logged params and artifacts to mlflow\n", + "2024-06-09 23:53:00,494 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:53:00,495 - GA_algo - INFO - ENTERING GENERATION 6\n", + "2024-06-09 23:53:00,496 - GA_algo - INFO - PAIRS ARE CREATED\n", + "2024-06-09 23:53:00,502 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:53:00,503 - root - INFO - Doing fitness calculating with individual {\"id\":\"dc3fbd9c-e713-4aaf-a9f6-2e7f003fdbf3\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,127.81269507937509,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":6,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:53:00,504 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:53:02,175 - root - INFO - Training is complete\n", + "2024-06-09 23:53:02,447 - root - INFO - Wow! all topics\n", + "2024-06-09 23:53:02,448 - root - INFO - Building dictionary\n", + "2024-06-09 23:53:02,680 - root - INFO - COMPONENTS 6.18333137236213 5.917344732418264\n", + "2024-06-09 23:53:03,023 - root - INFO - Fitness estimation took 2.52\n", + "2024-06-09 23:53:03,349 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:53:03,350 - root - INFO - Doing fitness calculating with individual {\"id\":\"1e458e78-0505-466e-b338-bc91bc0ad6e7\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.6065560125611166,0.6935414883927496,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":6,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:53:03,351 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:53:05,870 - root - INFO - Training is complete\n", + "2024-06-09 23:53:06,254 - root - INFO - Wow! all topics\n", + "2024-06-09 23:53:06,255 - root - INFO - Building dictionary\n", + "2024-06-09 23:53:06,611 - root - INFO - COMPONENTS 6.188030901191902 5.8981057732722135\n", + "2024-06-09 23:53:07,060 - root - INFO - Fitness estimation took 3.71\n", + "2024-06-09 23:53:07,421 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:53:07,422 - root - INFO - Doing fitness calculating with individual {\"id\":\"bda1e8d3-91db-4459-8564-979048c28ae6\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.6935414883927496,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":6,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:53:07,422 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:53:10,230 - root - INFO - Training is complete\n", + "2024-06-09 23:53:10,650 - root - INFO - Wow! all topics\n", + "2024-06-09 23:53:10,651 - root - INFO - Building dictionary\n", + "2024-06-09 23:53:11,047 - root - INFO - COMPONENTS 6.1814880221685735 5.8981057732722135\n", + "2024-06-09 23:53:11,546 - root - INFO - Fitness estimation took 4.12\n", + "2024-06-09 23:53:11,926 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:53:11,927 - root - INFO - Doing fitness calculating with individual {\"id\":\"ca2bd78c-2c73-406c-8e00-a7ee76435d58\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.46738007747537214,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":6,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:53:11,928 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:53:13,096 - root - INFO - Training is complete\n", + "2024-06-09 23:53:13,301 - root - INFO - Wow! all topics\n", + "2024-06-09 23:53:13,302 - root - INFO - Building dictionary\n", + "2024-06-09 23:53:13,473 - root - INFO - COMPONENTS 6.181608210338693 5.8523015349710885\n", + "2024-06-09 23:53:13,754 - root - INFO - Fitness estimation took 1.83\n", + "2024-06-09 23:53:14,057 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:53:14,058 - root - INFO - Doing fitness calculating with individual {\"id\":\"26112c3a-4857-49e9-acb8-bbda40bf23be\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.6065560125611166,0.6935414883927496,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":6,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:53:14,058 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:53:15,500 - root - INFO - Training is complete\n", + "2024-06-09 23:53:15,741 - root - INFO - Wow! all topics\n", + "2024-06-09 23:53:15,742 - root - INFO - Building dictionary\n", + "2024-06-09 23:53:15,950 - root - INFO - COMPONENTS 6.175792415342114 5.854526196544299\n", + "2024-06-09 23:53:16,264 - root - INFO - Fitness estimation took 2.21\n", + "2024-06-09 23:53:16,578 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:53:16,579 - root - INFO - Doing fitness calculating with individual {\"id\":\"dbc10658-b1f8-4c61-bfa1-9c54325da7ac\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":6,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:53:16,580 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:53:19,546 - root - INFO - Training is complete\n", + "2024-06-09 23:53:19,973 - root - INFO - Wow! all topics\n", + "2024-06-09 23:53:19,974 - root - INFO - Building dictionary\n", + "2024-06-09 23:53:20,381 - root - INFO - COMPONENTS 6.144127193609111 5.3358458740980765\n", + "2024-06-09 23:53:20,890 - root - INFO - Fitness estimation took 4.31\n", + "2024-06-09 23:53:21,279 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:53:21,280 - root - INFO - Doing fitness calculating with individual {\"id\":\"4866f136-3dd1-4b77-a450-6f1d4f16f8a5\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[21,-208.08637371442603,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":6,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:53:21,281 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:53:22,917 - root - INFO - Training is complete\n", + "2024-06-09 23:53:23,188 - root - INFO - Wow! all topics\n", + "2024-06-09 23:53:23,189 - root - INFO - Building dictionary\n", + "2024-06-09 23:53:23,416 - root - INFO - COMPONENTS 6.187896925587603 5.917344732418264\n", + "2024-06-09 23:53:23,753 - root - INFO - Fitness estimation took 2.47\n", + "2024-06-09 23:53:24,082 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:53:24,083 - root - INFO - Doing fitness calculating with individual {\"id\":\"d7810a29-016f-482f-ab33-68a536b2b96a\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":6,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:53:24,084 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:53:28,119 - root - INFO - Training is complete\n", + "2024-06-09 23:53:28,705 - root - INFO - Wow! all topics\n", + "2024-06-09 23:53:28,706 - root - INFO - Building dictionary\n", + "2024-06-09 23:53:29,288 - root - INFO - COMPONENTS 6.181756063843047 5.8736574800087595\n", + "2024-06-09 23:53:29,951 - root - INFO - Fitness estimation took 5.87\n", + "2024-06-09 23:53:30,388 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:53:30,389 - root - INFO - Doing fitness calculating with individual {\"id\":\"173854c8-08e9-4691-b789-62f15c5415f0\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.053890396724473266,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":6,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:53:30,390 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:53:33,292 - root - INFO - Training is complete\n", + "2024-06-09 23:53:33,737 - root - INFO - Wow! all topics\n", + "2024-06-09 23:53:33,738 - root - INFO - Building dictionary\n", + "2024-06-09 23:53:34,150 - root - INFO - COMPONENTS 6.1814880221685735 5.8981057732722135\n", + "2024-06-09 23:53:34,656 - root - INFO - Fitness estimation took 4.27\n", + "2024-06-09 23:53:35,060 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:53:35,061 - root - INFO - Doing fitness calculating with individual {\"id\":\"8ff0c3ee-413f-4213-b903-c6de1b450840\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":6,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:53:35,062 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:53:38,255 - root - INFO - Training is complete\n", + "2024-06-09 23:53:38,729 - root - INFO - Wow! all topics\n", + "2024-06-09 23:53:38,730 - root - INFO - Building dictionary\n", + "2024-06-09 23:53:39,188 - root - INFO - COMPONENTS 6.186599255429156 5.917344732418264\n", + "2024-06-09 23:53:39,734 - root - INFO - Fitness estimation took 4.67\n", + "2024-06-09 23:53:40,135 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:53:40,136 - root - INFO - Doing fitness calculating with individual {\"id\":\"d0005c85-8e6f-4119-8254-e4728108f5e9\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":6,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:53:40,137 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:53:42,851 - root - INFO - Training is complete\n", + "2024-06-09 23:53:43,237 - root - INFO - Wow! all topics\n", + "2024-06-09 23:53:43,238 - root - INFO - Building dictionary\n", + "2024-06-09 23:53:43,604 - root - INFO - COMPONENTS 6.163261087877551 5.865278052523317\n", + "2024-06-09 23:53:44,076 - root - INFO - Fitness estimation took 3.94\n", + "2024-06-09 23:53:44,450 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:53:44,450 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:53:44,451 - GA_algo - INFO - size of the new generation is 11\n", + "2024-06-09 23:53:44,452 - GA_algo - INFO - CROSSOVER IS OVER\n", + "2024-06-09 23:53:44,778 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:53:44,780 - root - INFO - Doing fitness calculating with individual {\"id\":\"9decaaf8-d7e4-408d-b06b-1088cdebfccf\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,160.58930630686314,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":6,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:53:44,781 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:53:46,735 - root - INFO - Training is complete\n", + "2024-06-09 23:53:47,035 - root - INFO - Wow! all topics\n", + "2024-06-09 23:53:47,036 - root - INFO - Building dictionary\n", + "2024-06-09 23:53:47,299 - root - INFO - COMPONENTS 6.1733481581213585 5.82923675666261\n", + "2024-06-09 23:53:47,673 - root - INFO - Fitness estimation took 2.89\n", + "2024-06-09 23:53:48,001 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:53:48,002 - root - INFO - Doing fitness calculating with individual {\"id\":\"ec0eb514-d318-4c88-b41a-c704b8a02e34\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,-65.64929494687078,308.6036509031194]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.6065560125611166,0.6935414883927496,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":6,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:53:48,003 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:53:50,514 - root - INFO - Training is complete\n", + "2024-06-09 23:53:50,891 - root - INFO - Wow! all topics\n", + "2024-06-09 23:53:50,892 - root - INFO - Building dictionary\n", + "2024-06-09 23:53:51,238 - root - INFO - COMPONENTS 6.169236933196979 5.753180522235598\n", + "2024-06-09 23:53:51,693 - root - INFO - Fitness estimation took 3.69\n", + "2024-06-09 23:53:52,062 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:53:52,063 - root - INFO - Doing fitness calculating with individual {\"id\":\"b6376175-d295-4cbf-8146-5c8bbcfa6ad1\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.27666195686304595,0.023236064737381823]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":6,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:53:52,064 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:53:53,980 - root - INFO - Training is complete\n", + "2024-06-09 23:53:54,283 - root - INFO - Wow! all topics\n", + "2024-06-09 23:53:54,284 - root - INFO - Building dictionary\n", + "2024-06-09 23:53:54,540 - root - INFO - COMPONENTS 6.203270604231911 5.885853870558686\n", + "2024-06-09 23:53:54,918 - root - INFO - Fitness estimation took 2.85\n", + "2024-06-09 23:53:55,251 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:53:55,252 - root - INFO - Doing fitness calculating with individual {\"id\":\"82065c0e-5af8-4680-afbe-78624d0af2ea\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[24,801.1976147352364,491.7621825116362]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.6935414883927496,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":6,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:53:55,252 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:53:57,863 - root - INFO - Training is complete\n", + "2024-06-09 23:53:58,255 - root - INFO - Wow! all topics\n", + "2024-06-09 23:53:58,256 - root - INFO - Building dictionary\n", + "2024-06-09 23:53:58,619 - root - INFO - COMPONENTS 6.1789457389343285 5.885853870558686\n", + "2024-06-09 23:53:59,091 - root - INFO - Fitness estimation took 3.84\n", + "2024-06-09 23:53:59,461 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:53:59,462 - root - INFO - Doing fitness calculating with individual {\"id\":\"76bd4e52-c589-4316-9a37-b6ddf4bef378\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[26,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,127.81269507937509,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":6,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:53:59,463 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:54:01,061 - root - INFO - Training is complete\n", + "2024-06-09 23:54:01,319 - root - INFO - Wow! all topics\n", + "2024-06-09 23:54:01,319 - root - INFO - Building dictionary\n", + "2024-06-09 23:54:01,559 - root - INFO - COMPONENTS 6.178094596805117 5.806005454099055\n", + "2024-06-09 23:54:01,894 - root - INFO - Fitness estimation took 2.43\n", + "2024-06-09 23:54:02,219 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:54:02,220 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:54:02,221 - GA_algo - INFO - MUTATION IS OVER\n", + "2024-06-09 23:54:02,222 - GA_algo - INFO - Population len 11. Best params so far: pipeline=Pipeline(stages=[Stage(stage_type=StageType(name='SparseThetaRegularizer', params=[Param(name='n', distribution=IntRangeDistribution(low=1, high=30)), Param(name='SparsePhi', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0)), Param(name='SparseTheta', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0))]), values=[12, 862.6766687279264, 135.15287388864226])], required_params=Stage(stage_type=StageType(name='General', params=[Param(name='basic_topics_count', distribution=IntRangeDistribution(low=0, high=5)), Param(name='ext_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_elem_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_mutation_selector', distribution=FloatRangeDistribution(low=0.0, high=1.0))]), values=[0, 0.6065560125611166, 0.6935414883927496, 0.4825868764489578])), with fitness: 12.126965949662853.ITERATION TIME: 61.727407932281494DATASET __noname__.TOPICS NUM 25.RUN ID ee461a46-d514-43d0-952a-8b6c87bc1818.\n", + "2024-06-09 23:54:02,223 - root - INFO - Sending a best individual to be logged\n", + "2024-06-09 23:54:02,224 - root - INFO - Doing fitness calculating with individual {\"id\":\"5c2c8a77-5695-49f1-afc8-978c7264d5e9\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":{\"avg_coherence_score\":12.126965949662853,\"perplexityScore\":1367.0140380859375,\"backgroundTokensRatioScore\":0.05860655754804611,\"contrast\":0.0,\"purity\":0.0,\"kernelSize\":0.0,\"npmi_50_list\":null,\"npmi_50\":null,\"sparsity_phi\":0.0,\"sparsity_theta\":0.0,\"topic_significance_uni\":null,\"topic_significance_vacuous\":null,\"topic_significance_back\":null,\"switchP_list\":[NaN],\"switchP\":NaN,\"all_topics\":true,\"coherence_10_list\":[6.847273399192251,6.730724307314206,6.81015328161727,6.781480270718103,6.77694276559601,6.415694418173986,6.5402244804936425,6.782087644950563,6.701378569528667,6.856104842127825,6.715258904023474,6.906832410962406,6.805157772835139,6.784559318540944,6.71502212100932,6.917367857924914,6.698414702271158,6.991365593236741,6.723793753535029,6.907165820793221,6.855182938882594,6.705875024615536,6.736505993320824,6.436080993913767,6.685136164271975],\"coherence_10\":6.753031333993983,\"coherence_15_list\":[6.533259130184876,6.7434837491616255,6.676293077333751,6.622572816911698,6.634785696596075,6.524346738566347,6.807546066213145,6.815954094691511,6.616734862340504,6.806680003129368,6.7020103275216725,6.761203755026397,6.717342134701922,6.8652863809880085,6.50350987427352,6.7755456749933485,6.60972623815657,6.706803361581337,6.70538407883765,6.668008457557744,6.787711817480435,6.382209451443663,6.501393967308762,6.636975246871754,6.661356405379554],\"coherence_15\":6.67064493629005,\"coherence_20_list\":[6.543529778298098,6.659106257405972,6.55089693627856,6.601624053428274,6.477956477788523,6.584763982393815,6.656955728438524,6.712728119404426,6.725730382236146,6.699997856014576,6.718095271814978,6.702235053167015,6.847602816557056,6.783694536761621,6.496320847180677,6.8217283570841225,6.573961657039192,6.615320972439311,6.640206956571775,6.635693031269098,6.601603508474884,6.564475729543362,6.402111263533532,6.540205951744872,6.718571003168364],\"coherence_20\":6.635004661121472,\"coherence_25_list\":[6.4562658078034,6.59966394892218,6.630403748877014,6.690951976281171,6.488971781028378,6.577738053891906,6.523056981418214,6.723446755987442,6.718751309089274,6.5988511561993475,6.653573921873519,6.449681069821281,6.749235806281429,6.670130443377854,6.515019948150179,6.644008902225608,6.548021815408342,6.6152028000627165,6.50265717472447,6.585544502416424,6.5788085660430635,6.556676378307134,6.432315960631782,6.482272836867887,6.570576649251297],\"coherence_25\":6.582473131797652,\"coherence_30_list\":[6.498301850613089,6.522535683163357,6.49412486825226,6.572057095606508,6.4021018511757735,6.46322155791618,6.416418018786766,6.612127580417481,6.660997116306298,6.538956654187582,6.5562471519261605,6.430528212033041,6.465225422306231,6.466394285190932,6.441010902849499,6.589092563683,6.598103637604237,6.554074123829485,6.521299828945756,6.4539040677744,6.555482680895484,6.557706911577103,6.423998047441563,6.473138026882254,6.397376493040208],\"coherence_30\":6.506576985296187,\"coherence_35_list\":[6.403993328955538,6.462154149778253,6.440989520026369,6.4165717176204735,6.344841496274747,6.370768144675219,6.324671198303996,6.551281980225318,6.444174891534814,6.417394427334757,6.437859139213485,6.324413395987504,6.374993912044886,6.452615949237499,6.391256217156041,6.5181892514292326,6.419554682954688,6.51480769332043,6.4332619550790024,6.392868815504892,6.450582928822726,6.408463110518769,6.220838899490337,6.448118184151123,6.308714264986353],\"coherence_35\":6.410935170185058,\"coherence_40_list\":[6.30776544475684,6.440888689958534,6.393979992768134,6.297851305062039,6.322423057973425,6.239924453458568,6.3006782655132785,6.4747793056016185,6.3901285235578875,6.431380765162843,6.387165109423467,6.2123813395574,6.338190936249873,6.286209005533212,6.344914954513021,6.428270985096164,6.358408527484597,6.447132442119591,6.364551711901957,6.3073312319138894,6.1900493234735325,6.248089748961348,6.175713956500994,6.387114894051671,6.20572081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+ "2024-06-09 23:54:02,225 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:54:02,841 - root - INFO - Training is complete\n", + "2024-06-09 23:54:02,980 - root - INFO - Wow! all topics\n", + "2024-06-09 23:54:02,981 - root - INFO - Building dictionary\n", + "2024-06-09 23:54:03,086 - root - INFO - COMPONENTS 6.180834003352823 5.94613194631003\n", + "2024-06-09 23:54:03,303 - root - INFO - Fitness estimation took 1.08\n", + "2024-06-09 23:54:03,524 - root - INFO - Logging params and artifacts to mlflow\n", + "2024-06-09 23:54:03,525 - root - INFO - Created experiment_0\n", + "2024-06-09 23:54:03,544 - root - INFO - Experiment exists, omitting creation\n", + "2024-06-09 23:54:03,544 - root - INFO - Experiment run name: fitness-__noname__-a0c9c67f-b5e0-4da7-9cf0-6266535d1981_tmp_6\n", + "2024-06-09 23:54:03,623 - root - DEBUG - Params dict: {'0_General_basic_topics_count': 0, '0_General_ext_mutation_prob': 0.6065560125611166, '0_General_ext_elem_mutation_prob': 0.6935414883927496, '0_General_ext_mutation_selector': 0.4825868764489578, '1_SparseThetaRegularizer_n': 12, '1_SparseThetaRegularizer_SparsePhi': 862.6766687279264, '1_SparseThetaRegularizer_SparseTheta': 135.15287388864226}\n", + "2024-06-09 23:54:04,174 - root - INFO - Logged params and artifacts to mlflow\n", + "2024-06-09 23:54:04,230 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:54:04,231 - GA_algo - INFO - ENTERING GENERATION 7\n", + "2024-06-09 23:54:04,232 - GA_algo - INFO - PAIRS ARE CREATED\n", + "2024-06-09 23:54:04,246 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:54:04,247 - root - INFO - Doing fitness calculating with individual {\"id\":\"15a73f46-b1bd-495f-8286-f9ca6e92fca1\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,127.81269507937509,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:54:04,248 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:54:05,144 - root - INFO - Training is complete\n", + "2024-06-09 23:54:05,312 - root - INFO - Wow! all topics\n", + "2024-06-09 23:54:05,313 - root - INFO - Building dictionary\n", + "2024-06-09 23:54:05,447 - root - INFO - COMPONENTS 6.18554727196262 5.852301534971088\n", + "2024-06-09 23:54:05,694 - root - INFO - Fitness estimation took 1.45\n", + "2024-06-09 23:54:05,980 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:54:05,981 - root - INFO - Doing fitness calculating with individual {\"id\":\"2d19b24e-51df-4dc7-a36d-1cee60a46e0f\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[26,-208.08637371442603,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:54:05,982 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:54:07,253 - root - INFO - Training is complete\n", + "2024-06-09 23:54:07,469 - root - INFO - Wow! all topics\n", + "2024-06-09 23:54:07,470 - root - INFO - Building dictionary\n", + "2024-06-09 23:54:07,656 - root - INFO - COMPONENTS 6.179248636978366 5.917344732418264\n", + "2024-06-09 23:54:07,948 - root - INFO - Fitness estimation took 1.97\n", + "2024-06-09 23:54:08,254 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:54:08,254 - root - INFO - Doing fitness calculating with individual {\"id\":\"da220383-6c43-4e89-8eb6-f4328a42b7f2\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.053890396724473266,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:54:08,255 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:54:11,697 - root - INFO - Training is complete\n", + "2024-06-09 23:54:12,219 - root - INFO - Wow! all topics\n", + "2024-06-09 23:54:12,220 - root - INFO - Building dictionary\n", + "2024-06-09 23:54:12,718 - root - INFO - COMPONENTS 6.188957533238761 5.917344732418264\n", + "2024-06-09 23:54:13,316 - root - INFO - Fitness estimation took 5.06\n", + "2024-06-09 23:54:13,735 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:54:13,735 - root - INFO - Doing fitness calculating with individual {\"id\":\"bdef662a-ca30-4d74-86d3-87f70042ecc9\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.6935414883927496,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:54:13,736 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:54:15,169 - root - INFO - Training is complete\n", + "2024-06-09 23:54:15,411 - root - INFO - Wow! all topics\n", + "2024-06-09 23:54:15,412 - root - INFO - Building dictionary\n", + "2024-06-09 23:54:15,626 - root - INFO - COMPONENTS 6.169403230192717 5.885853870558686\n", + "2024-06-09 23:54:15,945 - root - INFO - Fitness estimation took 2.21\n", + "2024-06-09 23:54:16,260 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:54:16,261 - root - INFO - Doing fitness calculating with individual {\"id\":\"073c783a-7f39-4f05-887b-87b7d239fa6d\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[24,801.1976147352364,491.7621825116362]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.20382144321324902,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:54:16,262 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:54:18,031 - root - INFO - Training is complete\n", + "2024-06-09 23:54:18,319 - root - INFO - Wow! all topics\n", + "2024-06-09 23:54:18,319 - root - INFO - Building dictionary\n", + "2024-06-09 23:54:18,563 - root - INFO - COMPONENTS 6.180588459792168 5.8523015349710885\n", + "2024-06-09 23:54:18,917 - root - INFO - Fitness estimation took 2.65\n", + "2024-06-09 23:54:19,253 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:54:19,255 - root - INFO - Doing fitness calculating with individual {\"id\":\"ee4bfbce-ea8c-4f5f-87aa-85b3ddfe7823\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:54:19,255 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:54:25,240 - root - INFO - Training is complete\n", + "2024-06-09 23:54:26,099 - root - INFO - Wow! all topics\n", + "2024-06-09 23:54:26,100 - root - INFO - Building dictionary\n", + "2024-06-09 23:54:26,937 - root - INFO - COMPONENTS 6.053460111571453 4.956459687622378\n", + "2024-06-09 23:54:27,832 - root - INFO - Fitness estimation took 8.58\n", + "2024-06-09 23:54:28,372 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:54:28,373 - root - INFO - Doing fitness calculating with individual {\"id\":\"cf2bef1c-262a-4c81-9bf7-51ade41c64e9\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:54:28,374 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:54:29,000 - root - INFO - Training is complete\n", + "2024-06-09 23:54:29,142 - root - INFO - Wow! all topics\n", + "2024-06-09 23:54:29,143 - root - INFO - Building dictionary\n", + "2024-06-09 23:54:29,254 - root - INFO - COMPONENTS 6.171324797363046 5.854526196544299\n", + "2024-06-09 23:54:29,469 - root - INFO - Fitness estimation took 1.10\n", + "2024-06-09 23:54:29,756 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:54:29,757 - root - INFO - Doing fitness calculating with individual {\"id\":\"aa9996c2-cd9e-4f78-addf-b36683bcc42c\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.20382144321324902,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:54:29,758 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:54:33,622 - root - INFO - Training is complete\n", + "2024-06-09 23:54:34,162 - root - INFO - Wow! all topics\n", + "2024-06-09 23:54:34,163 - root - INFO - Building dictionary\n", + "2024-06-09 23:54:34,691 - root - INFO - COMPONENTS 6.140322557382178 5.49281912208765\n", + "2024-06-09 23:54:35,309 - root - INFO - Fitness estimation took 5.55\n", + "2024-06-09 23:54:35,735 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:54:35,736 - root - INFO - Doing fitness calculating with individual {\"id\":\"5fd2c2c6-6886-499a-a80b-1f36a0f5d285\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.46738007747537214,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:54:35,737 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:54:36,927 - root - INFO - Training is complete\n", + "2024-06-09 23:54:37,130 - root - INFO - Wow! all topics\n", + "2024-06-09 23:54:37,131 - root - INFO - Building dictionary\n", + "2024-06-09 23:54:37,302 - root - INFO - COMPONENTS 6.181608210338693 5.8523015349710885\n", + "2024-06-09 23:54:37,583 - root - INFO - Fitness estimation took 1.85\n", + "2024-06-09 23:54:37,883 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:54:37,884 - root - INFO - Doing fitness calculating with individual {\"id\":\"ae21e386-7af0-4c8e-92bf-c5a36a69fc98\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.6935414883927496,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:54:37,884 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:54:40,720 - root - INFO - Training is complete\n", + "2024-06-09 23:54:41,134 - root - INFO - Wow! all topics\n", + "2024-06-09 23:54:41,135 - root - INFO - Building dictionary\n", + "2024-06-09 23:54:41,531 - root - INFO - COMPONENTS 6.1814880221685735 5.8981057732722135\n", + "2024-06-09 23:54:42,034 - root - INFO - Fitness estimation took 4.15\n", + "2024-06-09 23:54:42,424 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:54:42,425 - root - INFO - Doing fitness calculating with individual {\"id\":\"a55fc30e-47f4-4b18-ab07-2cc4d7912067\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[24,801.1976147352364,491.7621825116362]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.6935414883927496,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:54:42,425 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:54:45,662 - root - INFO - Training is complete\n", + "2024-06-09 23:54:46,138 - root - INFO - Wow! all topics\n", + "2024-06-09 23:54:46,139 - root - INFO - Building dictionary\n", + "2024-06-09 23:54:46,599 - root - INFO - COMPONENTS 6.181534959120463 5.8981057732722135\n", + "2024-06-09 23:54:47,153 - root - INFO - Fitness estimation took 4.73\n", + "2024-06-09 23:54:47,552 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:54:47,553 - root - INFO - Doing fitness calculating with individual {\"id\":\"d5a1df94-27ac-441f-ba4d-0937cb18ff88\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:54:47,554 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:54:48,935 - root - INFO - Training is complete\n", + "2024-06-09 23:54:49,163 - root - INFO - Wow! all topics\n", + "2024-06-09 23:54:49,164 - root - INFO - Building dictionary\n", + "2024-06-09 23:54:49,360 - root - INFO - COMPONENTS 6.1836703992916515 5.829236756662609\n", + "2024-06-09 23:54:49,667 - root - INFO - Fitness estimation took 2.11\n", + "2024-06-09 23:54:49,972 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:54:49,973 - root - INFO - Doing fitness calculating with individual {\"id\":\"accad46e-2e6f-422b-80e4-866d9ab3403d\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:54:49,974 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:54:52,584 - root - INFO - Training is complete\n", + "2024-06-09 23:54:52,977 - root - INFO - Wow! all topics\n", + "2024-06-09 23:54:52,977 - root - INFO - Building dictionary\n", + "2024-06-09 23:54:53,351 - root - INFO - COMPONENTS 6.18095395500894 5.8981057732722135\n", + "2024-06-09 23:54:53,823 - root - INFO - Fitness estimation took 3.85\n", + "2024-06-09 23:54:54,192 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:54:54,193 - root - INFO - Doing fitness calculating with individual {\"id\":\"9152fed3-dc45-444d-864c-386d1eb46c91\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[24,801.1976147352364,491.7621825116362]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.6935414883927496,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:54:54,194 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:54:56,812 - root - INFO - Training is complete\n", + "2024-06-09 23:54:57,204 - root - INFO - Wow! all topics\n", + "2024-06-09 23:54:57,205 - root - INFO - Building dictionary\n", + "2024-06-09 23:54:57,575 - root - INFO - COMPONENTS 6.1789457389343285 5.885853870558686\n", + "2024-06-09 23:54:58,047 - root - INFO - Fitness estimation took 3.85\n", + "2024-06-09 23:54:58,418 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:54:58,419 - root - INFO - Doing fitness calculating with individual {\"id\":\"d65b8952-2802-4612-8062-7084b13b523a\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:54:58,420 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:55:01,867 - root - INFO - Training is complete\n", + "2024-06-09 23:55:02,388 - root - INFO - Wow! all topics\n", + "2024-06-09 23:55:02,389 - root - INFO - Building dictionary\n", + "2024-06-09 23:55:02,863 - root - INFO - COMPONENTS 6.188957533238761 5.917344732418264\n", + "2024-06-09 23:55:03,439 - root - INFO - Fitness estimation took 5.02\n", + "2024-06-09 23:55:03,859 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:55:03,860 - root - INFO - Doing fitness calculating with individual {\"id\":\"30ed952c-5bd2-4d7a-a3ee-9dd90ffba0ea\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:55:03,861 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:55:07,201 - root - INFO - Training is complete\n", + "2024-06-09 23:55:07,686 - root - INFO - Wow! all topics\n", + "2024-06-09 23:55:07,687 - root - INFO - Building dictionary\n", + "2024-06-09 23:55:08,169 - root - INFO - COMPONENTS 6.16141511963253 5.593561567749961\n", + "2024-06-09 23:55:08,744 - root - INFO - Fitness estimation took 4.88\n", + "2024-06-09 23:55:09,156 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:55:09,158 - root - INFO - Doing fitness calculating with individual {\"id\":\"00dc7e37-cdbc-4c8b-ae9f-9c877185dc1f\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.27666195686304595,0.023236064737381823]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:55:09,159 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:55:11,139 - root - INFO - Training is complete\n", + "2024-06-09 23:55:11,439 - root - INFO - Wow! all topics\n", + "2024-06-09 23:55:11,440 - root - INFO - Building dictionary\n", + "2024-06-09 23:55:11,715 - root - INFO - COMPONENTS 6.184179232395791 5.82923675666261\n", + "2024-06-09 23:55:12,095 - root - INFO - Fitness estimation took 2.94\n", + "2024-06-09 23:55:12,422 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:55:12,423 - root - INFO - Doing fitness calculating with individual {\"id\":\"4b0dd563-de02-4c1a-b1dc-aa7c877de945\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.6935414883927496,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:55:12,424 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:55:15,906 - root - INFO - Training is complete\n", + "2024-06-09 23:55:16,415 - root - INFO - Wow! all topics\n", + "2024-06-09 23:55:16,416 - root - INFO - Building dictionary\n", + "2024-06-09 23:55:16,904 - root - INFO - COMPONENTS 6.186072819671218 5.8981057732722135\n", + "2024-06-09 23:55:17,488 - root - INFO - Fitness estimation took 5.06\n", + "2024-06-09 23:55:17,903 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:55:17,904 - root - INFO - Doing fitness calculating with individual {\"id\":\"83b626dc-a894-421c-b13b-326e363d1e22\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:55:17,905 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:55:21,047 - root - INFO - Training is complete\n", + "2024-06-09 23:55:21,505 - root - INFO - Wow! all topics\n", + "2024-06-09 23:55:21,507 - root - INFO - Building dictionary\n", + "2024-06-09 23:55:21,949 - root - INFO - COMPONENTS 6.177058177355759 5.8736574800087595\n", + "2024-06-09 23:55:22,488 - root - INFO - Fitness estimation took 4.58\n", + "2024-06-09 23:55:22,889 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:55:22,890 - root - INFO - Doing fitness calculating with individual {\"id\":\"bbabf4c5-ba1c-4ae7-a826-5d1b8757d8c4\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,127.81269507937509,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.6935414883927496,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:55:22,891 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:55:27,446 - root - INFO - Training is complete\n", + "2024-06-09 23:55:28,117 - root - INFO - Wow! all topics\n", + "2024-06-09 23:55:28,118 - root - INFO - Building dictionary\n", + "2024-06-09 23:55:28,784 - root - INFO - COMPONENTS 6.092723239026085 5.099469433280663\n", + "2024-06-09 23:55:29,515 - root - INFO - Fitness estimation took 6.62\n", + "2024-06-09 23:55:30,002 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:55:30,003 - root - INFO - Doing fitness calculating with individual {\"id\":\"10a4bf6c-517d-45cd-8cbe-8167066e8927\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.46738007747537214,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:55:30,003 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:55:30,614 - root - INFO - Training is complete\n", + "2024-06-09 23:55:30,756 - root - INFO - Wow! all topics\n", + "2024-06-09 23:55:30,757 - root - INFO - Building dictionary\n", + "2024-06-09 23:55:30,860 - root - INFO - COMPONENTS 6.180834003352823 5.94613194631003\n", + "2024-06-09 23:55:31,075 - root - INFO - Fitness estimation took 1.07\n", + "2024-06-09 23:55:31,361 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:55:31,362 - root - INFO - Doing fitness calculating with individual {\"id\":\"913f1f7a-98ff-4a4e-9bc3-4dd85cfcb1c0\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:55:31,363 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:55:31,978 - root - INFO - Training is complete\n", + "2024-06-09 23:55:32,114 - root - INFO - Wow! all topics\n", + "2024-06-09 23:55:32,115 - root - INFO - Building dictionary\n", + "2024-06-09 23:55:32,218 - root - INFO - COMPONENTS 6.180834003352823 5.94613194631003\n", + "2024-06-09 23:55:32,432 - root - INFO - Fitness estimation took 1.07\n", + "2024-06-09 23:55:32,712 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:55:32,713 - root - INFO - Doing fitness calculating with individual {\"id\":\"3831f3e2-007a-4d0c-9bf1-66697ca994c2\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,160.58930630686314,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:55:32,714 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:55:34,707 - root - INFO - Training is complete\n", + "2024-06-09 23:55:35,008 - root - INFO - Wow! all topics\n", + "2024-06-09 23:55:35,009 - root - INFO - Building dictionary\n", + "2024-06-09 23:55:35,285 - root - INFO - COMPONENTS 6.1733481581213585 5.82923675666261\n", + "2024-06-09 23:55:35,660 - root - INFO - Fitness estimation took 2.95\n", + "2024-06-09 23:55:35,991 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:55:35,992 - root - INFO - Doing fitness calculating with individual {\"id\":\"4746a816-cc41-4810-bca8-a73f6a699c63\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,-65.64929494687078,308.6036509031194]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:55:35,993 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:55:36,600 - root - INFO - Training is complete\n", + "2024-06-09 23:55:36,737 - root - INFO - Wow! all topics\n", + "2024-06-09 23:55:36,738 - root - INFO - Building dictionary\n", + "2024-06-09 23:55:36,848 - root - INFO - COMPONENTS 6.185758791782396 5.82923675666261\n", + "2024-06-09 23:55:37,066 - root - INFO - Fitness estimation took 1.07\n", + "2024-06-09 23:55:37,337 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:55:37,338 - root - INFO - Doing fitness calculating with individual {\"id\":\"88508b4b-0112-4088-b1e6-122117382e70\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[1,0.6065560125611166,0.6935414883927496,0.9834148204803567]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:55:37,338 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:55:39,856 - root - INFO - Training is complete\n", + "2024-06-09 23:55:40,233 - root - INFO - Wow! all topics\n", + "2024-06-09 23:55:40,234 - root - INFO - Building dictionary\n", + "2024-06-09 23:55:40,583 - root - INFO - COMPONENTS 6.188030901191902 5.8981057732722135\n", + "2024-06-09 23:55:41,036 - root - INFO - Fitness estimation took 3.70\n", + "2024-06-09 23:55:41,399 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:55:41,400 - root - INFO - Doing fitness calculating with individual {\"id\":\"35e82b36-f7e0-4d1d-b0df-383e57cba264\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,127.81269507937509,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:55:41,401 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:55:42,288 - root - INFO - Training is complete\n", + "2024-06-09 23:55:42,458 - root - INFO - Wow! all topics\n", + "2024-06-09 23:55:42,459 - root - INFO - Building dictionary\n", + "2024-06-09 23:55:42,596 - root - INFO - COMPONENTS 6.18554727196262 5.852301534971088\n", + "2024-06-09 23:55:42,854 - root - INFO - Fitness estimation took 1.45\n", + "2024-06-09 23:55:43,149 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:55:43,151 - root - INFO - Doing fitness calculating with individual {\"id\":\"8b171d4e-f9d4-4961-b181-2a285be2e2f0\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:55:43,151 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:55:44,548 - root - INFO - Training is complete\n", + "2024-06-09 23:55:44,781 - root - INFO - Wow! all topics\n", + "2024-06-09 23:55:44,782 - root - INFO - Building dictionary\n", + "2024-06-09 23:55:44,977 - root - INFO - COMPONENTS 6.19478889563721 5.885853870558685\n", + "2024-06-09 23:55:45,279 - root - INFO - Fitness estimation took 2.13\n", + "2024-06-09 23:55:45,588 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:55:45,588 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:55:45,590 - GA_algo - INFO - size of the new generation is 27\n", + "2024-06-09 23:55:45,591 - GA_algo - INFO - CROSSOVER IS OVER\n", + "2024-06-09 23:55:45,901 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:55:45,902 - root - INFO - Doing fitness calculating with individual {\"id\":\"8b511c39-6cef-4e47-8452-22bb510078db\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[5,0.8498300271994074,0.46738007747537214,0.19353397167024533]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:55:45,903 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:55:46,558 - root - INFO - Training is complete\n", + "2024-06-09 23:55:46,709 - root - INFO - Wow! all topics\n", + "2024-06-09 23:55:46,710 - root - INFO - Building dictionary\n", + "2024-06-09 23:55:46,834 - root - INFO - COMPONENTS 6.172440228491896 5.854526196544299\n", + "2024-06-09 23:55:47,062 - root - INFO - Fitness estimation took 1.16\n", + "2024-06-09 23:55:47,367 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:55:47,368 - root - INFO - Doing fitness calculating with individual {\"id\":\"5e3fc5ba-c323-4d1b-a415-e786514952c4\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:55:47,369 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:55:49,379 - root - INFO - Training is complete\n", + "2024-06-09 23:55:49,698 - root - INFO - Wow! all topics\n", + "2024-06-09 23:55:49,699 - root - INFO - Building dictionary\n", + "2024-06-09 23:55:49,984 - root - INFO - COMPONENTS 6.177241647042988 5.885853870558686\n", + "2024-06-09 23:55:50,377 - root - INFO - Fitness estimation took 3.01\n", + "2024-06-09 23:55:50,721 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:55:50,722 - root - INFO - Doing fitness calculating with individual {\"id\":\"3acf0c86-3919-4038-8869-aea21e166336\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,127.81269507937509,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:55:50,722 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:55:52,396 - root - INFO - Training is complete\n", + "2024-06-09 23:55:52,666 - root - INFO - Wow! all topics\n", + "2024-06-09 23:55:52,667 - root - INFO - Building dictionary\n", + "2024-06-09 23:55:52,899 - root - INFO - COMPONENTS 6.1781791984118115 5.917344732418264\n", + "2024-06-09 23:55:53,252 - root - INFO - Fitness estimation took 2.53\n", + "2024-06-09 23:55:53,575 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:55:53,576 - root - INFO - Doing fitness calculating with individual {\"id\":\"0d9adee3-9737-47f6-8dd6-e4d929a720e1\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[18,862.6766687279264,966.3506156656272]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.6935414883927496,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:55:53,577 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:55:57,380 - root - INFO - Training is complete\n", + "2024-06-09 23:55:57,934 - root - INFO - Wow! all topics\n", + "2024-06-09 23:55:57,936 - root - INFO - Building dictionary\n", + "2024-06-09 23:55:58,459 - root - INFO - COMPONENTS 6.187673051867611 5.8981057732722135\n", + "2024-06-09 23:55:59,085 - root - INFO - Fitness estimation took 5.51\n", + "2024-06-09 23:55:59,512 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:55:59,513 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:55:59,514 - GA_algo - INFO - MUTATION IS OVER\n", + "2024-06-09 23:55:59,514 - GA_algo - INFO - Population len 11. Best params so far: pipeline=Pipeline(stages=[Stage(stage_type=StageType(name='SparseThetaRegularizer', params=[Param(name='n', distribution=IntRangeDistribution(low=1, high=30)), Param(name='SparsePhi', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0)), Param(name='SparseTheta', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0))]), values=[12, 862.6766687279264, 135.15287388864226])], required_params=Stage(stage_type=StageType(name='General', params=[Param(name='basic_topics_count', distribution=IntRangeDistribution(low=0, high=5)), Param(name='ext_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_elem_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_mutation_selector', distribution=FloatRangeDistribution(low=0.0, high=1.0))]), values=[0, 0.6065560125611166, 0.6935414883927496, 0.4825868764489578])), with fitness: 12.126965949662853.ITERATION TIME: 115.28335762023926DATASET __noname__.TOPICS NUM 25.RUN ID ee461a46-d514-43d0-952a-8b6c87bc1818.\n", + "2024-06-09 23:55:59,515 - root - INFO - Sending a best individual to be logged\n", + "2024-06-09 23:55:59,516 - root - INFO - Doing fitness calculating with individual {\"id\":\"5c2c8a77-5695-49f1-afc8-978c7264d5e9\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":{\"avg_coherence_score\":12.126965949662853,\"perplexityScore\":1367.0140380859375,\"backgroundTokensRatioScore\":0.05860655754804611,\"contrast\":0.0,\"purity\":0.0,\"kernelSize\":0.0,\"npmi_50_list\":null,\"npmi_50\":null,\"sparsity_phi\":0.0,\"sparsity_theta\":0.0,\"topic_significance_uni\":null,\"topic_significance_vacuous\":null,\"topic_significance_back\":null,\"switchP_list\":[NaN],\"switchP\":NaN,\"all_topics\":true,\"coherence_10_list\":[6.847273399192251,6.730724307314206,6.81015328161727,6.781480270718103,6.77694276559601,6.415694418173986,6.5402244804936425,6.782087644950563,6.701378569528667,6.856104842127825,6.715258904023474,6.906832410962406,6.805157772835139,6.784559318540944,6.71502212100932,6.917367857924914,6.698414702271158,6.991365593236741,6.723793753535029,6.907165820793221,6.855182938882594,6.705875024615536,6.736505993320824,6.436080993913767,6.685136164271975],\"coherence_10\":6.753031333993983,\"coherence_15_list\":[6.533259130184876,6.7434837491616255,6.676293077333751,6.622572816911698,6.634785696596075,6.524346738566347,6.807546066213145,6.815954094691511,6.616734862340504,6.806680003129368,6.7020103275216725,6.761203755026397,6.717342134701922,6.8652863809880085,6.50350987427352,6.7755456749933485,6.60972623815657,6.706803361581337,6.70538407883765,6.668008457557744,6.787711817480435,6.382209451443663,6.501393967308762,6.636975246871754,6.661356405379554],\"coherence_15\":6.67064493629005,\"coherence_20_list\":[6.543529778298098,6.659106257405972,6.55089693627856,6.601624053428274,6.477956477788523,6.584763982393815,6.656955728438524,6.712728119404426,6.725730382236146,6.699997856014576,6.718095271814978,6.702235053167015,6.847602816557056,6.783694536761621,6.496320847180677,6.8217283570841225,6.573961657039192,6.615320972439311,6.640206956571775,6.635693031269098,6.601603508474884,6.564475729543362,6.402111263533532,6.540205951744872,6.718571003168364],\"coherence_20\":6.635004661121472,\"coherence_25_list\":[6.4562658078034,6.59966394892218,6.630403748877014,6.690951976281171,6.488971781028378,6.577738053891906,6.523056981418214,6.723446755987442,6.718751309089274,6.5988511561993475,6.653573921873519,6.449681069821281,6.749235806281429,6.670130443377854,6.515019948150179,6.644008902225608,6.548021815408342,6.6152028000627165,6.50265717472447,6.585544502416424,6.5788085660430635,6.556676378307134,6.432315960631782,6.482272836867887,6.570576649251297],\"coherence_25\":6.582473131797652,\"coherence_30_list\":[6.498301850613089,6.522535683163357,6.49412486825226,6.572057095606508,6.4021018511757735,6.46322155791618,6.416418018786766,6.612127580417481,6.660997116306298,6.538956654187582,6.5562471519261605,6.430528212033041,6.465225422306231,6.466394285190932,6.441010902849499,6.589092563683,6.598103637604237,6.554074123829485,6.521299828945756,6.4539040677744,6.555482680895484,6.557706911577103,6.423998047441563,6.473138026882254,6.397376493040208],\"coherence_30\":6.506576985296187,\"coherence_35_list\":[6.403993328955538,6.462154149778253,6.440989520026369,6.4165717176204735,6.344841496274747,6.370768144675219,6.324671198303996,6.551281980225318,6.444174891534814,6.417394427334757,6.437859139213485,6.324413395987504,6.374993912044886,6.452615949237499,6.391256217156041,6.5181892514292326,6.419554682954688,6.51480769332043,6.4332619550790024,6.392868815504892,6.450582928822726,6.408463110518769,6.220838899490337,6.448118184151123,6.308714264986353],\"coherence_35\":6.410935170185058,\"coherence_40_list\":[6.30776544475684,6.440888689958534,6.393979992768134,6.297851305062039,6.322423057973425,6.239924453458568,6.3006782655132785,6.4747793056016185,6.3901285235578875,6.431380765162843,6.387165109423467,6.2123813395574,6.338190936249873,6.286209005533212,6.344914954513021,6.428270985096164,6.358408527484597,6.447132442119591,6.364551711901957,6.3073312319138894,6.1900493234735325,6.248089748961348,6.175713956500994,6.387114894051671,6.205720811567557],\"coherence_40\":6.331241791286456,\"coherence_45_list\":[6.196164221994946,6.351691112650757,6.3876871616475634,6.2169367259764,6.2700687095415955,6.154446551697229,6.17751286550516,6.497909083831898,6.350876703135634,6.353290419225084,6.273368257422746,6.10877835770136,6.125628963460158,6.163246233493589,6.285113911098988,6.387130315208957,6.27931548552275,6.413741896156556,6.239117383936755,6.292372700874718,6.092104690588711,6.243802338228963,6.118583431499146,6.301566496512477,6.146092099903227],\"coherence_45\":6.257061844672615,\"coherence_50_list\":[6.148699935315383,6.326911028321904,6.239947269495553,6.184194116344167,6.213987750895649,6.154614045231385,6.101080248667447,6.408587979920304,6.254104246981741,6.249013718990919,6.265822702728159,6.0037499668126015,6.018770607969764,6.1650329870269305,6.180272942662255,6.25422435765407,6.166204569308145,6.334086157926717,6.170494242529895,6.236511466949228,6.050193270336161,6.1273842321012815,5.94613194631003,6.209544392561376,6.111285900779486],\"coherence_50\":6.180834003352823,\"coherence_55_list\":[6.153647478055628,6.28603684260796,6.212023155321504,6.1382169485543345,6.074421697343837,6.104739726572959,6.051968223883241,6.169135553843967,6.195168094416744,6.242748775556229,6.199417846435927,5.9910717059339165,6.025975591178977,6.014461955408583,6.089510694517783,6.102852534309653,6.113577271330549,6.245489116366203,6.099461673251516,6.111546243466477,5.994337079709307,6.072900822653464,5.803431514985174,6.111547412573434,6.055213608917615],\"coherence_55\":6.1063560626878,\"npmi_15\":null,\"npmi_25\":null},\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":7,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:55:59,517 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:56:00,121 - root - INFO - Training is complete\n", + "2024-06-09 23:56:00,260 - root - INFO - Wow! all topics\n", + "2024-06-09 23:56:00,261 - root - INFO - Building dictionary\n", + "2024-06-09 23:56:00,364 - root - INFO - COMPONENTS 6.180834003352823 5.94613194631003\n", + "2024-06-09 23:56:00,581 - root - INFO - Fitness estimation took 1.06\n", + "2024-06-09 23:56:00,807 - root - INFO - Logging params and artifacts to mlflow\n", + "2024-06-09 23:56:00,808 - root - INFO - Created experiment_0\n", + "2024-06-09 23:56:00,827 - root - INFO - Experiment exists, omitting creation\n", + "2024-06-09 23:56:00,828 - root - INFO - Experiment run name: fitness-__noname__-ee000ab4-c0e0-4e05-b138-40e4286e90ac_tmp_7\n", + "2024-06-09 23:56:00,905 - root - DEBUG - Params dict: {'0_General_basic_topics_count': 0, '0_General_ext_mutation_prob': 0.6065560125611166, '0_General_ext_elem_mutation_prob': 0.6935414883927496, '0_General_ext_mutation_selector': 0.4825868764489578, '1_SparseThetaRegularizer_n': 12, '1_SparseThetaRegularizer_SparsePhi': 862.6766687279264, '1_SparseThetaRegularizer_SparseTheta': 135.15287388864226}\n", + "2024-06-09 23:56:01,413 - root - INFO - Logged params and artifacts to mlflow\n", + "2024-06-09 23:56:01,474 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:56:01,475 - GA_algo - INFO - ENTERING GENERATION 8\n", + "2024-06-09 23:56:01,476 - GA_algo - INFO - PAIRS ARE CREATED\n", + "2024-06-09 23:56:01,485 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:56:01,486 - root - INFO - Doing fitness calculating with individual {\"id\":\"86e0614c-511f-4cd9-9315-a158d80106c5\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,127.81269507937509,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:56:01,487 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:56:03,719 - root - INFO - Training is complete\n", + "2024-06-09 23:56:04,062 - root - INFO - Wow! all topics\n", + "2024-06-09 23:56:04,063 - root - INFO - Building dictionary\n", + "2024-06-09 23:56:04,375 - root - INFO - COMPONENTS 6.164917255098811 5.917344732418264\n", + "2024-06-09 23:56:04,788 - root - INFO - Fitness estimation took 3.30\n", + "2024-06-09 23:56:05,145 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:56:05,146 - root - INFO - Doing fitness calculating with individual {\"id\":\"d77c24db-aa85-4391-b531-fc2f740d5029\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,127.81269507937509,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:56:05,147 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:56:07,408 - root - INFO - Training is complete\n", + "2024-06-09 23:56:07,742 - root - INFO - Wow! all topics\n", + "2024-06-09 23:56:07,743 - root - INFO - Building dictionary\n", + "2024-06-09 23:56:08,049 - root - INFO - COMPONENTS 6.164917255098811 5.917344732418264\n", + "2024-06-09 23:56:08,460 - root - INFO - Fitness estimation took 3.31\n", + "2024-06-09 23:56:08,808 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:56:08,809 - root - INFO - Doing fitness calculating with individual {\"id\":\"42887867-ad5b-48dd-a290-af86e4dc3b9a\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[5,0.8498300271994074,0.46738007747537214,0.19353397167024533]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:56:08,810 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:56:10,073 - root - INFO - Training is complete\n", + "2024-06-09 23:56:10,305 - root - INFO - Wow! all topics\n", + "2024-06-09 23:56:10,306 - root - INFO - Building dictionary\n", + "2024-06-09 23:56:10,510 - root - INFO - COMPONENTS 6.181877012179996 5.854526196544299\n", + "2024-06-09 23:56:10,818 - root - INFO - Fitness estimation took 2.01\n", + "2024-06-09 23:56:11,149 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:56:11,150 - root - INFO - Doing fitness calculating with individual {\"id\":\"1813fe50-6abd-4349-900d-dc5f06a646b3\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:56:11,151 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:56:14,202 - root - INFO - Training is complete\n", + "2024-06-09 23:56:14,638 - root - INFO - Wow! all topics\n", + "2024-06-09 23:56:14,639 - root - INFO - Building dictionary\n", + "2024-06-09 23:56:15,050 - root - INFO - COMPONENTS 6.159710682190097 5.844261057817623\n", + "2024-06-09 23:56:15,565 - root - INFO - Fitness estimation took 4.41\n", + "2024-06-09 23:56:15,947 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:56:15,948 - root - INFO - Doing fitness calculating with individual {\"id\":\"176f07f9-ac49-424e-856c-cfb262a9a04c\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:56:15,949 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:56:17,121 - root - INFO - Training is complete\n", + "2024-06-09 23:56:17,325 - root - INFO - Wow! all topics\n", + "2024-06-09 23:56:17,326 - root - INFO - Building dictionary\n", + "2024-06-09 23:56:17,498 - root - INFO - COMPONENTS 6.181608210338693 5.8523015349710885\n", + "2024-06-09 23:56:17,786 - root - INFO - Fitness estimation took 1.84\n", + "2024-06-09 23:56:18,085 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:56:18,086 - root - INFO - Doing fitness calculating with individual {\"id\":\"4ee962a2-adc0-4f6a-bea4-dfc48c018b7b\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:56:18,087 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:56:20,910 - root - INFO - Training is complete\n", + "2024-06-09 23:56:21,332 - root - INFO - Wow! all topics\n", + "2024-06-09 23:56:21,333 - root - INFO - Building dictionary\n", + "2024-06-09 23:56:21,731 - root - INFO - COMPONENTS 6.1814880221685735 5.8981057732722135\n", + "2024-06-09 23:56:22,230 - root - INFO - Fitness estimation took 4.14\n", + "2024-06-09 23:56:22,611 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:56:22,613 - root - INFO - Doing fitness calculating with individual {\"id\":\"c4de7cc7-5835-4930-9129-21c184a5713c\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:56:22,613 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:56:23,978 - root - INFO - Training is complete\n", + "2024-06-09 23:56:24,205 - root - INFO - Wow! all topics\n", + "2024-06-09 23:56:24,206 - root - INFO - Building dictionary\n", + "2024-06-09 23:56:24,401 - root - INFO - COMPONENTS 6.169084951089839 5.885853870558686\n", + "2024-06-09 23:56:24,711 - root - INFO - Fitness estimation took 2.10\n", + "2024-06-09 23:56:25,023 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:56:25,025 - root - INFO - Doing fitness calculating with individual {\"id\":\"6a7fa6bd-885e-4e67-b637-877bd7a7f362\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,127.81269507937509,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:56:25,025 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:56:25,928 - root - INFO - Training is complete\n", + "2024-06-09 23:56:26,099 - root - INFO - Wow! all topics\n", + "2024-06-09 23:56:26,100 - root - INFO - Building dictionary\n", + "2024-06-09 23:56:26,244 - root - INFO - COMPONENTS 6.18554727196262 5.852301534971088\n", + "2024-06-09 23:56:26,493 - root - INFO - Fitness estimation took 1.47\n", + "2024-06-09 23:56:26,783 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:56:26,784 - root - INFO - Doing fitness calculating with individual {\"id\":\"f92015c6-2f42-4bdd-a033-0191d3b280d6\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[18,862.6766687279264,966.3506156656272]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:56:26,785 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:56:31,047 - root - INFO - Training is complete\n", + "2024-06-09 23:56:31,628 - root - INFO - Wow! all topics\n", + "2024-06-09 23:56:31,629 - root - INFO - Building dictionary\n", + "2024-06-09 23:56:32,202 - root - INFO - COMPONENTS 6.152634231390525 5.4714365544053605\n", + "2024-06-09 23:56:32,868 - root - INFO - Fitness estimation took 6.08\n", + "2024-06-09 23:56:33,301 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:56:33,302 - root - INFO - Doing fitness calculating with individual {\"id\":\"af41d408-982a-48ba-8e3d-118c19e2f168\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:56:33,303 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:56:35,868 - root - INFO - Training is complete\n", + "2024-06-09 23:56:36,241 - root - INFO - Wow! all topics\n", + "2024-06-09 23:56:36,242 - root - INFO - Building dictionary\n", + "2024-06-09 23:56:36,587 - root - INFO - COMPONENTS 6.180889957727971 5.885853870558686\n", + "2024-06-09 23:56:37,038 - root - INFO - Fitness estimation took 3.74\n", + "2024-06-09 23:56:37,393 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:56:37,394 - root - INFO - Doing fitness calculating with individual {\"id\":\"a45b6bdc-ee0b-4089-95d7-5a181f75a96b\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:56:37,395 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:56:40,541 - root - INFO - Training is complete\n", + "2024-06-09 23:56:41,003 - root - INFO - Wow! all topics\n", + "2024-06-09 23:56:41,004 - root - INFO - Building dictionary\n", + "2024-06-09 23:56:41,470 - root - INFO - COMPONENTS 6.186599255429156 5.917344732418264\n", + "2024-06-09 23:56:42,017 - root - INFO - Fitness estimation took 4.62\n", + "2024-06-09 23:56:42,425 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:56:42,426 - root - INFO - Doing fitness calculating with individual {\"id\":\"b5e3292f-6d67-438b-a3d2-15777aa23e42\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:56:42,427 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:56:43,038 - root - INFO - Training is complete\n", + "2024-06-09 23:56:43,175 - root - INFO - Wow! all topics\n", + "2024-06-09 23:56:43,176 - root - INFO - Building dictionary\n", + "2024-06-09 23:56:43,280 - root - INFO - COMPONENTS 6.180834003352823 5.94613194631003\n", + "2024-06-09 23:56:43,499 - root - INFO - Fitness estimation took 1.07\n", + "2024-06-09 23:56:43,775 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:56:43,776 - root - INFO - Doing fitness calculating with individual {\"id\":\"bda8eea9-75ec-4cf6-b795-bb2324ba7735\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:56:43,776 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:56:48,364 - root - INFO - Training is complete\n", + "2024-06-09 23:56:49,012 - root - INFO - Wow! all topics\n", + "2024-06-09 23:56:49,013 - root - INFO - Building dictionary\n", + "2024-06-09 23:56:49,651 - root - INFO - COMPONENTS 6.135910383847443 5.420663628052357\n", + "2024-06-09 23:56:50,383 - root - INFO - Fitness estimation took 6.61\n", + "2024-06-09 23:56:50,851 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:56:50,852 - root - INFO - Doing fitness calculating with individual {\"id\":\"21473cce-3735-4cd2-944a-c3ca14d9d934\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:56:50,853 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:56:51,481 - root - INFO - Training is complete\n", + "2024-06-09 23:56:51,625 - root - INFO - Wow! all topics\n", + "2024-06-09 23:56:51,626 - root - INFO - Building dictionary\n", + "2024-06-09 23:56:51,741 - root - INFO - COMPONENTS 6.171324797363046 5.854526196544299\n", + "2024-06-09 23:56:51,962 - root - INFO - Fitness estimation took 1.11\n", + "2024-06-09 23:56:52,249 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:56:52,250 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:56:52,251 - GA_algo - INFO - size of the new generation is 14\n", + "2024-06-09 23:56:52,252 - GA_algo - INFO - CROSSOVER IS OVER\n", + "2024-06-09 23:56:52,543 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:56:52,544 - root - INFO - Doing fitness calculating with individual {\"id\":\"9664ebd9-5d97-45ed-96a9-6e44b08a9eb4\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.4359499149679452,0.985570101838968,0.28244250532055126]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:56:52,545 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:56:55,690 - root - INFO - Training is complete\n", + "2024-06-09 23:56:56,156 - root - INFO - Wow! all topics\n", + "2024-06-09 23:56:56,157 - root - INFO - Building dictionary\n", + "2024-06-09 23:56:56,599 - root - INFO - COMPONENTS 6.186599255429156 5.917344732418264\n", + "2024-06-09 23:56:57,156 - root - INFO - Fitness estimation took 4.61\n", + "2024-06-09 23:56:57,555 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:56:57,557 - root - INFO - Doing fitness calculating with individual {\"id\":\"8c6b809c-cd4e-43cb-8549-39a9d4f09317\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-393.58493989000556,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:56:57,557 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:57:00,716 - root - INFO - Training is complete\n", + "2024-06-09 23:57:01,188 - root - INFO - Wow! all topics\n", + "2024-06-09 23:57:01,189 - root - INFO - Building dictionary\n", + "2024-06-09 23:57:01,632 - root - INFO - COMPONENTS 6.1666985727489525 5.6433954210700685\n", + "2024-06-09 23:57:02,173 - root - INFO - Fitness estimation took 4.62\n", + "2024-06-09 23:57:02,568 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:57:02,569 - root - INFO - Doing fitness calculating with individual {\"id\":\"1df46c9b-9b08-4ac9-a655-e085dd12969c\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,127.81269507937509,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.5987960491423391,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:57:02,570 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:57:04,911 - root - INFO - Training is complete\n", + "2024-06-09 23:57:05,265 - root - INFO - Wow! all topics\n", + "2024-06-09 23:57:05,267 - root - INFO - Building dictionary\n", + "2024-06-09 23:57:05,591 - root - INFO - COMPONENTS 6.183270126564992 5.917344732418264\n", + "2024-06-09 23:57:06,029 - root - INFO - Fitness estimation took 3.46\n", + "2024-06-09 23:57:06,387 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:57:06,389 - root - INFO - Doing fitness calculating with individual {\"id\":\"890540bd-a54f-42ac-aa7e-b0c680b3a0f6\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,881.1694946738041]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,127.81269507937509,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:57:06,389 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:57:08,632 - root - INFO - Training is complete\n", + "2024-06-09 23:57:08,978 - root - INFO - Wow! all topics\n", + "2024-06-09 23:57:08,979 - root - INFO - Building dictionary\n", + "2024-06-09 23:57:09,279 - root - INFO - COMPONENTS 6.182915156673046 5.885853870558686\n", + "2024-06-09 23:57:09,694 - root - INFO - Fitness estimation took 3.30\n", + "2024-06-09 23:57:10,053 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:57:10,054 - root - INFO - Doing fitness calculating with individual {\"id\":\"cad4d284-429f-466c-880e-91e1d1b86911\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.8066675211580605,0.8793124625020681,0.7238629361718627]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":8,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:57:10,055 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:57:12,681 - root - INFO - Training is complete\n", + "2024-06-09 23:57:13,087 - root - INFO - Wow! all topics\n", + "2024-06-09 23:57:13,088 - root - INFO - Building dictionary\n", + "2024-06-09 23:57:13,468 - root - INFO - COMPONENTS 6.18095395500894 5.8981057732722135\n", + "2024-06-09 23:57:13,951 - root - INFO - Fitness estimation took 3.90\n", + "2024-06-09 23:57:14,329 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:57:14,330 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:57:14,331 - GA_algo - INFO - MUTATION IS OVER\n", + "2024-06-09 23:57:14,332 - GA_algo - INFO - Population len 11. Best params so far: pipeline=Pipeline(stages=[Stage(stage_type=StageType(name='SparseThetaRegularizer', params=[Param(name='n', distribution=IntRangeDistribution(low=1, high=30)), Param(name='SparsePhi', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0)), Param(name='SparseTheta', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0))]), values=[12, 862.6766687279264, 135.15287388864226])], required_params=Stage(stage_type=StageType(name='General', params=[Param(name='basic_topics_count', distribution=IntRangeDistribution(low=0, high=5)), Param(name='ext_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_elem_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_mutation_selector', distribution=FloatRangeDistribution(low=0.0, high=1.0))]), values=[0, 0.6065560125611166, 0.6935414883927496, 0.4825868764489578])), with fitness: 12.126965949662853.ITERATION TIME: 72.85677480697632DATASET __noname__.TOPICS NUM 25.RUN ID ee461a46-d514-43d0-952a-8b6c87bc1818.\n", + "2024-06-09 23:57:14,332 - root - INFO - Sending a best individual to be logged\n", + "2024-06-09 23:57:14,333 - root - INFO - Doing fitness calculating with individual {\"id\":\"5c2c8a77-5695-49f1-afc8-978c7264d5e9\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":{\"avg_coherence_score\":12.126965949662853,\"perplexityScore\":1367.0140380859375,\"backgroundTokensRatioScore\":0.05860655754804611,\"contrast\":0.0,\"purity\":0.0,\"kernelSize\":0.0,\"npmi_50_list\":null,\"npmi_50\":null,\"sparsity_phi\":0.0,\"sparsity_theta\":0.0,\"topic_significance_uni\":null,\"topic_significance_vacuous\":null,\"topic_significance_back\":null,\"switchP_list\":[NaN],\"switchP\":NaN,\"all_topics\":true,\"coherence_10_list\":[6.847273399192251,6.730724307314206,6.81015328161727,6.781480270718103,6.77694276559601,6.415694418173986,6.5402244804936425,6.782087644950563,6.701378569528667,6.856104842127825,6.715258904023474,6.906832410962406,6.805157772835139,6.784559318540944,6.71502212100932,6.917367857924914,6.698414702271158,6.991365593236741,6.723793753535029,6.907165820793221,6.855182938882594,6.705875024615536,6.736505993320824,6.436080993913767,6.685136164271975],\"coherence_10\":6.753031333993983,\"coherence_15_list\":[6.533259130184876,6.7434837491616255,6.676293077333751,6.622572816911698,6.634785696596075,6.524346738566347,6.807546066213145,6.815954094691511,6.616734862340504,6.806680003129368,6.7020103275216725,6.761203755026397,6.717342134701922,6.8652863809880085,6.50350987427352,6.7755456749933485,6.60972623815657,6.706803361581337,6.70538407883765,6.668008457557744,6.787711817480435,6.382209451443663,6.501393967308762,6.636975246871754,6.661356405379554],\"coherence_15\":6.67064493629005,\"coherence_20_list\":[6.543529778298098,6.659106257405972,6.55089693627856,6.601624053428274,6.477956477788523,6.584763982393815,6.656955728438524,6.712728119404426,6.725730382236146,6.699997856014576,6.718095271814978,6.702235053167015,6.847602816557056,6.783694536761621,6.496320847180677,6.8217283570841225,6.573961657039192,6.615320972439311,6.640206956571775,6.635693031269098,6.601603508474884,6.564475729543362,6.402111263533532,6.540205951744872,6.718571003168364],\"coherence_20\":6.635004661121472,\"coherence_25_list\":[6.4562658078034,6.59966394892218,6.630403748877014,6.690951976281171,6.488971781028378,6.577738053891906,6.523056981418214,6.723446755987442,6.718751309089274,6.5988511561993475,6.653573921873519,6.449681069821281,6.749235806281429,6.670130443377854,6.515019948150179,6.644008902225608,6.548021815408342,6.6152028000627165,6.50265717472447,6.585544502416424,6.5788085660430635,6.556676378307134,6.432315960631782,6.482272836867887,6.570576649251297],\"coherence_25\":6.582473131797652,\"coherence_30_list\":[6.498301850613089,6.522535683163357,6.49412486825226,6.572057095606508,6.4021018511757735,6.46322155791618,6.416418018786766,6.612127580417481,6.660997116306298,6.538956654187582,6.5562471519261605,6.430528212033041,6.465225422306231,6.466394285190932,6.441010902849499,6.589092563683,6.598103637604237,6.554074123829485,6.521299828945756,6.4539040677744,6.555482680895484,6.557706911577103,6.423998047441563,6.473138026882254,6.397376493040208],\"coherence_30\":6.506576985296187,\"coherence_35_list\":[6.403993328955538,6.462154149778253,6.440989520026369,6.4165717176204735,6.344841496274747,6.370768144675219,6.324671198303996,6.551281980225318,6.444174891534814,6.417394427334757,6.437859139213485,6.324413395987504,6.374993912044886,6.452615949237499,6.391256217156041,6.5181892514292326,6.419554682954688,6.51480769332043,6.4332619550790024,6.392868815504892,6.450582928822726,6.408463110518769,6.220838899490337,6.448118184151123,6.308714264986353],\"coherence_35\":6.410935170185058,\"coherence_40_list\":[6.30776544475684,6.440888689958534,6.393979992768134,6.297851305062039,6.322423057973425,6.239924453458568,6.3006782655132785,6.4747793056016185,6.3901285235578875,6.431380765162843,6.387165109423467,6.2123813395574,6.338190936249873,6.286209005533212,6.344914954513021,6.428270985096164,6.358408527484597,6.447132442119591,6.364551711901957,6.3073312319138894,6.1900493234735325,6.248089748961348,6.175713956500994,6.387114894051671,6.20572081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+ "2024-06-09 23:57:14,334 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:57:14,935 - root - INFO - Training is complete\n", + "2024-06-09 23:57:15,071 - root - INFO - Wow! all topics\n", + "2024-06-09 23:57:15,072 - root - INFO - Building dictionary\n", + "2024-06-09 23:57:15,181 - root - INFO - COMPONENTS 6.180834003352823 5.94613194631003\n", + "2024-06-09 23:57:15,401 - root - INFO - Fitness estimation took 1.07\n", + "2024-06-09 23:57:15,621 - root - INFO - Logging params and artifacts to mlflow\n", + "2024-06-09 23:57:15,622 - root - INFO - Created experiment_0\n", + "2024-06-09 23:57:15,640 - root - INFO - Experiment exists, omitting creation\n", + "2024-06-09 23:57:15,641 - root - INFO - Experiment run name: fitness-__noname__-c5afce69-163c-417a-934c-6b783c1856bc_tmp_8\n", + "2024-06-09 23:57:15,714 - root - DEBUG - Params dict: {'0_General_basic_topics_count': 0, '0_General_ext_mutation_prob': 0.6065560125611166, '0_General_ext_elem_mutation_prob': 0.6935414883927496, '0_General_ext_mutation_selector': 0.4825868764489578, '1_SparseThetaRegularizer_n': 12, '1_SparseThetaRegularizer_SparsePhi': 862.6766687279264, '1_SparseThetaRegularizer_SparseTheta': 135.15287388864226}\n", + "2024-06-09 23:57:16,233 - root - INFO - Logged params and artifacts to mlflow\n", + "2024-06-09 23:57:16,295 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:57:16,296 - GA_algo - INFO - ENTERING GENERATION 9\n", + "2024-06-09 23:57:16,297 - GA_algo - INFO - PAIRS ARE CREATED\n", + "2024-06-09 23:57:16,313 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:57:16,314 - root - INFO - Doing fitness calculating with individual {\"id\":\"78b80f5c-ade4-4660-bf96-1534588c0909\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:57:16,315 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:57:18,270 - root - INFO - Training is complete\n", + "2024-06-09 23:57:18,566 - root - INFO - Wow! all topics\n", + "2024-06-09 23:57:18,567 - root - INFO - Building dictionary\n", + "2024-06-09 23:57:18,836 - root - INFO - COMPONENTS 6.171417894826951 5.879119074374357\n", + "2024-06-09 23:57:19,205 - root - INFO - Fitness estimation took 2.89\n", + "2024-06-09 23:57:19,536 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:57:19,537 - root - INFO - Doing fitness calculating with individual {\"id\":\"e3e7530e-2205-43a4-9727-89b40c0d53c6\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:57:19,538 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:57:23,093 - root - INFO - Training is complete\n", + "2024-06-09 23:57:23,623 - root - INFO - Wow! all topics\n", + "2024-06-09 23:57:23,624 - root - INFO - Building dictionary\n", + "2024-06-09 23:57:24,113 - root - INFO - COMPONENTS 6.186072819671218 5.8981057732722135\n", + "2024-06-09 23:57:24,699 - root - INFO - Fitness estimation took 5.16\n", + "2024-06-09 23:57:25,117 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:57:25,119 - root - INFO - Doing fitness calculating with individual {\"id\":\"66a31b65-f672-4a57-99fc-f8a3e99552c1\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.4359499149679452,0.985570101838968,0.28244250532055126]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:57:25,119 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:57:27,680 - root - INFO - Training is complete\n", + "2024-06-09 23:57:28,058 - root - INFO - Wow! all topics\n", + "2024-06-09 23:57:28,059 - root - INFO - Building dictionary\n", + "2024-06-09 23:57:28,412 - root - INFO - COMPONENTS 6.18380197886387 5.917344732418264\n", + "2024-06-09 23:57:28,870 - root - INFO - Fitness estimation took 3.75\n", + "2024-06-09 23:57:29,241 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:57:29,242 - root - INFO - Doing fitness calculating with individual {\"id\":\"8a923dce-f6e6-404a-afb1-3c80aa7f9b53\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:57:29,243 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:57:31,203 - root - INFO - Training is complete\n", + "2024-06-09 23:57:31,499 - root - INFO - Wow! all topics\n", + "2024-06-09 23:57:31,500 - root - INFO - Building dictionary\n", + "2024-06-09 23:57:31,770 - root - INFO - COMPONENTS 6.165598549008693 5.782129153168337\n", + "2024-06-09 23:57:32,147 - root - INFO - Fitness estimation took 2.90\n", + "2024-06-09 23:57:32,485 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:57:32,486 - root - INFO - Doing fitness calculating with individual {\"id\":\"f0e24037-b449-49fa-9bf2-8447ca3f5959\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:57:32,486 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:57:36,397 - root - INFO - Training is complete\n", + "2024-06-09 23:57:36,939 - root - INFO - Wow! all topics\n", + "2024-06-09 23:57:36,940 - root - INFO - Building dictionary\n", + "2024-06-09 23:57:37,478 - root - INFO - COMPONENTS 6.146404999112138 5.644880165336658\n", + "2024-06-09 23:57:38,111 - root - INFO - Fitness estimation took 5.62\n", + "2024-06-09 23:57:38,540 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:57:38,541 - root - INFO - Doing fitness calculating with individual {\"id\":\"03604328-b8b6-45c8-b45c-b61aa43121e2\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.46738007747537214,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:57:38,542 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:57:39,731 - root - INFO - Training is complete\n", + "2024-06-09 23:57:39,938 - root - INFO - Wow! all topics\n", + "2024-06-09 23:57:39,939 - root - INFO - Building dictionary\n", + "2024-06-09 23:57:40,112 - root - INFO - COMPONENTS 6.181608210338693 5.8523015349710885\n", + "2024-06-09 23:57:40,396 - root - INFO - Fitness estimation took 1.85\n", + "2024-06-09 23:57:40,698 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:57:40,699 - root - INFO - Doing fitness calculating with individual {\"id\":\"3a44b578-aa4d-4722-93f5-d5ac058c68a3\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.053890396724473266,0.6935414883927496,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:57:40,699 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:57:43,524 - root - INFO - Training is complete\n", + "2024-06-09 23:57:43,950 - root - INFO - Wow! all topics\n", + "2024-06-09 23:57:43,951 - root - INFO - Building dictionary\n", + "2024-06-09 23:57:44,363 - root - INFO - COMPONENTS 6.1814880221685735 5.8981057732722135\n", + "2024-06-09 23:57:44,874 - root - INFO - Fitness estimation took 4.18\n", + "2024-06-09 23:57:45,293 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:57:45,294 - root - INFO - Doing fitness calculating with individual {\"id\":\"68727fc8-025c-4d40-9047-496648341e9f\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.053890396724473266,0.6935414883927496,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:57:45,295 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:57:49,321 - root - INFO - Training is complete\n", + "2024-06-09 23:57:49,920 - root - INFO - Wow! all topics\n", + "2024-06-09 23:57:49,921 - root - INFO - Building dictionary\n", + "2024-06-09 23:57:50,504 - root - INFO - COMPONENTS 6.180789372910162 5.8736574800087595\n", + "2024-06-09 23:57:51,186 - root - INFO - Fitness estimation took 5.89\n", + "2024-06-09 23:57:51,633 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:57:51,634 - root - INFO - Doing fitness calculating with individual {\"id\":\"4dd3647d-268e-4e23-abe1-1ca3796eb889\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,127.81269507937509,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.5987960491423391,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:57:51,635 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:57:56,872 - root - INFO - Training is complete\n", + "2024-06-09 23:57:57,620 - root - INFO - Wow! all topics\n", + "2024-06-09 23:57:57,621 - root - INFO - Building dictionary\n", + "2024-06-09 23:57:58,335 - root - INFO - COMPONENTS 6.083879433139958 5.128839936134757\n", + "2024-06-09 23:57:59,136 - root - INFO - Fitness estimation took 7.50\n", + "2024-06-09 23:57:59,635 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:57:59,636 - root - INFO - Doing fitness calculating with individual {\"id\":\"bbc8ea3d-002b-41b2-b526-90f626a8f0be\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.46738007747537214,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:57:59,636 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:58:00,277 - root - INFO - Training is complete\n", + "2024-06-09 23:58:00,420 - root - INFO - Wow! all topics\n", + "2024-06-09 23:58:00,421 - root - INFO - Building dictionary\n", + "2024-06-09 23:58:00,531 - root - INFO - COMPONENTS 6.171324797363046 5.854526196544299\n", + "2024-06-09 23:58:00,751 - root - INFO - Fitness estimation took 1.12\n", + "2024-06-09 23:58:01,037 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:58:01,038 - root - INFO - Doing fitness calculating with individual {\"id\":\"76b8cca5-edb0-4bcb-afef-0aa9ea6139fb\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:58:01,038 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:58:04,499 - root - INFO - Training is complete\n", + "2024-06-09 23:58:05,011 - root - INFO - Wow! all topics\n", + "2024-06-09 23:58:05,013 - root - INFO - Building dictionary\n", + "2024-06-09 23:58:05,509 - root - INFO - COMPONENTS 6.188957533238761 5.917344732418264\n", + "2024-06-09 23:58:06,091 - root - INFO - Fitness estimation took 5.05\n", + "2024-06-09 23:58:06,503 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:58:06,504 - root - INFO - Doing fitness calculating with individual {\"id\":\"0793db27-db70-4e83-ad83-0a2915636c8f\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.8066675211580605,0.8793124625020681,0.7238629361718627]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:58:06,504 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:58:09,181 - root - INFO - Training is complete\n", + "2024-06-09 23:58:09,589 - root - INFO - Wow! all topics\n", + "2024-06-09 23:58:09,590 - root - INFO - Building dictionary\n", + "2024-06-09 23:58:09,979 - root - INFO - COMPONENTS 6.18095395500894 5.8981057732722135\n", + "2024-06-09 23:58:10,465 - root - INFO - Fitness estimation took 3.96\n", + "2024-06-09 23:58:10,844 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:58:10,845 - root - INFO - Doing fitness calculating with individual {\"id\":\"1517ec65-67ba-414f-bb1c-0d3431f79070\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,127.81269507937509,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:58:10,846 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:58:11,739 - root - INFO - Training is complete\n", + "2024-06-09 23:58:11,909 - root - INFO - Wow! all topics\n", + "2024-06-09 23:58:11,910 - root - INFO - Building dictionary\n", + "2024-06-09 23:58:12,047 - root - INFO - COMPONENTS 6.18554727196262 5.852301534971088\n", + "2024-06-09 23:58:12,296 - root - INFO - Fitness estimation took 1.45\n", + "2024-06-09 23:58:12,582 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:58:12,583 - root - INFO - Doing fitness calculating with individual {\"id\":\"96f09aa5-2caa-47f1-a63f-3326ea5fe0c5\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.5987960491423391,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:58:12,584 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:58:14,595 - root - INFO - Training is complete\n", + "2024-06-09 23:58:14,910 - root - INFO - Wow! all topics\n", + "2024-06-09 23:58:14,911 - root - INFO - Building dictionary\n", + "2024-06-09 23:58:15,202 - root - INFO - COMPONENTS 6.186739836239295 5.8981057732722135\n", + "2024-06-09 23:58:15,595 - root - INFO - Fitness estimation took 3.01\n", + "2024-06-09 23:58:15,942 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:58:15,943 - root - INFO - Doing fitness calculating with individual {\"id\":\"cb2426ab-31c4-4350-95eb-6a5ae3f6171d\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:58:15,944 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:58:19,228 - root - INFO - Training is complete\n", + "2024-06-09 23:58:19,692 - root - INFO - Wow! all topics\n", + "2024-06-09 23:58:19,693 - root - INFO - Building dictionary\n", + "2024-06-09 23:58:20,156 - root - INFO - COMPONENTS 6.15095761987465 5.644880165336659\n", + "2024-06-09 23:58:20,715 - root - INFO - Fitness estimation took 4.77\n", + "2024-06-09 23:58:21,118 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:58:21,119 - root - INFO - Doing fitness calculating with individual {\"id\":\"10032c02-21c9-4396-83c6-05edb2596588\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:58:21,120 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:58:25,977 - root - INFO - Training is complete\n", + "2024-06-09 23:58:26,673 - root - INFO - Wow! all topics\n", + "2024-06-09 23:58:26,674 - root - INFO - Building dictionary\n", + "2024-06-09 23:58:27,341 - root - INFO - COMPONENTS 6.133514802718029 5.3618500109255685\n", + "2024-06-09 23:58:28,085 - root - INFO - Fitness estimation took 6.97\n", + "2024-06-09 23:58:28,559 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:58:28,560 - root - INFO - Doing fitness calculating with individual {\"id\":\"94bde9b3-a729-43f0-b59f-0e71fa944414\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.8066675211580605,0.8793124625020681,0.7238629361718627]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:58:28,561 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:58:29,801 - root - INFO - Training is complete\n", + "2024-06-09 23:58:30,021 - root - INFO - Wow! all topics\n", + "2024-06-09 23:58:30,022 - root - INFO - Building dictionary\n", + "2024-06-09 23:58:30,217 - root - INFO - COMPONENTS 6.181877012179996 5.854526196544299\n", + "2024-06-09 23:58:30,514 - root - INFO - Fitness estimation took 1.95\n", + "2024-06-09 23:58:30,833 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:58:30,834 - root - INFO - Doing fitness calculating with individual {\"id\":\"656b9f9c-7ef2-4f4b-9529-6b11a8c876eb\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.8066675211580605,0.8793124625020681,0.7238629361718627]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:58:30,835 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:58:34,026 - root - INFO - Training is complete\n", + "2024-06-09 23:58:34,509 - root - INFO - Wow! all topics\n", + "2024-06-09 23:58:34,510 - root - INFO - Building dictionary\n", + "2024-06-09 23:58:34,974 - root - INFO - COMPONENTS 6.186272221208124 5.8981057732722135\n", + "2024-06-09 23:58:35,536 - root - INFO - Fitness estimation took 4.70\n", + "2024-06-09 23:58:35,940 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:58:35,941 - root - INFO - Doing fitness calculating with individual {\"id\":\"6500dc41-1448-4908-9e1d-a8c1a81d2b13\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:58:35,941 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:58:37,107 - root - INFO - Training is complete\n", + "2024-06-09 23:58:37,310 - root - INFO - Wow! all topics\n", + "2024-06-09 23:58:37,311 - root - INFO - Building dictionary\n", + "2024-06-09 23:58:37,482 - root - INFO - COMPONENTS 6.181608210338693 5.8523015349710885\n", + "2024-06-09 23:58:37,764 - root - INFO - Fitness estimation took 1.82\n", + "2024-06-09 23:58:38,063 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:58:38,064 - root - INFO - Doing fitness calculating with individual {\"id\":\"dc9d7db6-8f75-4602-9b54-a4610d10364b\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-393.58493989000556,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:58:38,065 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:58:40,671 - root - INFO - Training is complete\n", + "2024-06-09 23:58:41,052 - root - INFO - Wow! all topics\n", + "2024-06-09 23:58:41,053 - root - INFO - Building dictionary\n", + "2024-06-09 23:58:41,416 - root - INFO - COMPONENTS 6.173898281783851 5.806005454099053\n", + "2024-06-09 23:58:41,888 - root - INFO - Fitness estimation took 3.82\n", + "2024-06-09 23:58:42,260 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:58:42,261 - root - INFO - Doing fitness calculating with individual {\"id\":\"805be906-9f83-4c47-a744-3c5458fbd1c1\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:58:42,262 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:58:42,873 - root - INFO - Training is complete\n", + "2024-06-09 23:58:43,012 - root - INFO - Wow! all topics\n", + "2024-06-09 23:58:43,013 - root - INFO - Building dictionary\n", + "2024-06-09 23:58:43,123 - root - INFO - COMPONENTS 6.180834003352823 5.94613194631003\n", + "2024-06-09 23:58:43,342 - root - INFO - Fitness estimation took 1.08\n", + "2024-06-09 23:58:43,620 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:58:43,621 - root - INFO - Doing fitness calculating with individual {\"id\":\"37b6dc59-339e-4550-87d6-d13bbe7f9563\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.053890396724473266,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:58:43,622 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:58:47,017 - root - INFO - Training is complete\n", + "2024-06-09 23:58:47,536 - root - INFO - Wow! all topics\n", + "2024-06-09 23:58:47,537 - root - INFO - Building dictionary\n", + "2024-06-09 23:58:48,036 - root - INFO - COMPONENTS 6.188957533238761 5.917344732418264\n", + "2024-06-09 23:58:48,631 - root - INFO - Fitness estimation took 5.01\n", + "2024-06-09 23:58:49,048 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:58:49,049 - root - INFO - Doing fitness calculating with individual {\"id\":\"bff1dd57-686d-4671-976a-b5c1d8db6681\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.985570101838968,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:58:49,050 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:58:49,680 - root - INFO - Training is complete\n", + "2024-06-09 23:58:49,823 - root - INFO - Wow! all topics\n", + "2024-06-09 23:58:49,824 - root - INFO - Building dictionary\n", + "2024-06-09 23:58:49,935 - root - INFO - COMPONENTS 6.171324797363046 5.854526196544299\n", + "2024-06-09 23:58:50,153 - root - INFO - Fitness estimation took 1.10\n", + "2024-06-09 23:58:50,435 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:58:50,437 - root - INFO - Doing fitness calculating with individual {\"id\":\"91867eaf-1d9f-4f0e-a0a4-0861f5d9687c\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.4359499149679452,0.6935414883927496,0.28244250532055126]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:58:50,437 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:58:53,522 - root - INFO - Training is complete\n", + "2024-06-09 23:58:53,951 - root - INFO - Wow! all topics\n", + "2024-06-09 23:58:53,952 - root - INFO - Building dictionary\n", + "2024-06-09 23:58:54,362 - root - INFO - COMPONENTS 6.146770314711376 5.569628118463706\n", + "2024-06-09 23:58:54,871 - root - INFO - Fitness estimation took 4.43\n", + "2024-06-09 23:58:55,258 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:58:55,259 - root - INFO - Doing fitness calculating with individual {\"id\":\"8f0ef3e0-94a0-4421-bead-f34cb8c6e246\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,127.81269507937509,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:58:55,260 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:58:55,569 - root - INFO - Training is complete\n", + "2024-06-09 23:58:55,672 - root - INFO - Wow! all topics\n", + "2024-06-09 23:58:55,672 - root - INFO - Building dictionary\n", + "2024-06-09 23:58:55,741 - root - INFO - COMPONENTS 6.182009154639844 5.8523015349710885\n", + "2024-06-09 23:58:55,924 - root - INFO - Fitness estimation took 0.66\n", + "2024-06-09 23:58:56,190 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:58:56,191 - root - INFO - Doing fitness calculating with individual {\"id\":\"2ba25262-8f1c-43a0-bbdc-f1de8105580b\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.5987960491423391,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:58:56,191 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:58:58,830 - root - INFO - Training is complete\n", + "2024-06-09 23:58:59,225 - root - INFO - Wow! all topics\n", + "2024-06-09 23:58:59,226 - root - INFO - Building dictionary\n", + "2024-06-09 23:58:59,602 - root - INFO - COMPONENTS 6.187244739448101 5.917344732418264\n", + "2024-06-09 23:59:00,078 - root - INFO - Fitness estimation took 3.89\n", + "2024-06-09 23:59:00,452 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:59:00,453 - root - INFO - Doing fitness calculating with individual {\"id\":\"9fc4b66d-abc8-4061-a739-6c79193e7cb3\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:59:00,454 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:59:01,633 - root - INFO - Training is complete\n", + "2024-06-09 23:59:01,840 - root - INFO - Wow! all topics\n", + "2024-06-09 23:59:01,841 - root - INFO - Building dictionary\n", + "2024-06-09 23:59:02,013 - root - INFO - COMPONENTS 6.181608210338693 5.8523015349710885\n", + "2024-06-09 23:59:02,298 - root - INFO - Fitness estimation took 1.84\n", + "2024-06-09 23:59:02,603 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:59:02,604 - root - INFO - Doing fitness calculating with individual {\"id\":\"9c8190de-d5eb-408c-971e-e8a817e0c479\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:59:02,605 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:59:03,404 - root - INFO - Training is complete\n", + "2024-06-09 23:59:03,569 - root - INFO - Wow! all topics\n", + "2024-06-09 23:59:03,569 - root - INFO - Building dictionary\n", + "2024-06-09 23:59:03,696 - root - INFO - COMPONENTS 6.183937846824059 5.885853870558686\n", + "2024-06-09 23:59:03,931 - root - INFO - Fitness estimation took 1.33\n", + "2024-06-09 23:59:04,212 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:59:04,213 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:59:04,214 - GA_algo - INFO - size of the new generation is 28\n", + "2024-06-09 23:59:04,215 - GA_algo - INFO - CROSSOVER IS OVER\n", + "2024-06-09 23:59:04,528 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:59:04,530 - root - INFO - Doing fitness calculating with individual {\"id\":\"c3fa765f-a763-4b9e-8814-fe56e59eac79\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.053890396724473266,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:59:04,530 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:59:07,973 - root - INFO - Training is complete\n", + "2024-06-09 23:59:08,500 - root - INFO - Wow! all topics\n", + "2024-06-09 23:59:08,502 - root - INFO - Building dictionary\n", + "2024-06-09 23:59:09,003 - root - INFO - COMPONENTS 6.188957533238761 5.917344732418264\n", + "2024-06-09 23:59:09,595 - root - INFO - Fitness estimation took 5.07\n", + "2024-06-09 23:59:10,020 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:59:10,022 - root - INFO - Doing fitness calculating with individual {\"id\":\"f764330e-e377-4e0e-bf3c-cd1ef122c74c\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,872.1940678889505,294.9343944340262]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.5987960491423391,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:59:10,022 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:59:12,654 - root - INFO - Training is complete\n", + "2024-06-09 23:59:13,058 - root - INFO - Wow! all topics\n", + "2024-06-09 23:59:13,059 - root - INFO - Building dictionary\n", + "2024-06-09 23:59:13,425 - root - INFO - COMPONENTS 6.188961567996536 5.8981057732722135\n", + "2024-06-09 23:59:13,898 - root - INFO - Fitness estimation took 3.88\n", + "2024-06-09 23:59:14,274 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:59:14,275 - root - INFO - Doing fitness calculating with individual {\"id\":\"10b73028-2289-48c5-85ba-dbe85615f49a\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[5,0.08316206321031394,0.045754488640769475,0.8622486657466205]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:59:14,276 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:59:17,561 - root - INFO - Training is complete\n", + "2024-06-09 23:59:18,079 - root - INFO - Wow! all topics\n", + "2024-06-09 23:59:18,080 - root - INFO - Building dictionary\n", + "2024-06-09 23:59:18,583 - root - INFO - COMPONENTS 6.186599255429156 5.917344732418264\n", + "2024-06-09 23:59:19,170 - root - INFO - Fitness estimation took 4.89\n", + "2024-06-09 23:59:19,592 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:59:19,593 - root - INFO - Doing fitness calculating with individual {\"id\":\"05dd30b4-0d33-4797-966a-1cb715e4970f\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-228.46109226048748,-973.8523259591432]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.4359499149679452,0.985570101838968,0.28244250532055126]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:59:19,594 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:59:22,135 - root - INFO - Training is complete\n", + "2024-06-09 23:59:22,231 - root - INFO - Building dictionary\n", + "2024-06-09 23:59:22,277 - root - INFO - COMPONENTS 0.0 0\n", + "2024-06-09 23:59:22,306 - root - INFO - Fitness estimation took 2.71\n", + "2024-06-09 23:59:22,507 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:59:22,508 - root - INFO - Doing fitness calculating with individual {\"id\":\"2c5cf82a-89d1-455c-985f-28d610297592\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[14,-580.3569019472527,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.5987960491423391,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:59:22,508 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:59:24,555 - root - INFO - Training is complete\n", + "2024-06-09 23:59:24,801 - root - INFO - Building dictionary\n", + "2024-06-09 23:59:24,988 - root - INFO - COMPONENTS 0.0 0\n", + "2024-06-09 23:59:25,162 - root - INFO - Fitness estimation took 2.65\n", + "2024-06-09 23:59:25,384 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:59:25,384 - root - INFO - The fitness results have been obtained\n", + "2024-06-09 23:59:25,385 - GA_algo - INFO - MUTATION IS OVER\n", + "2024-06-09 23:59:25,386 - GA_algo - INFO - Population len 11. Best params so far: pipeline=Pipeline(stages=[Stage(stage_type=StageType(name='SparseThetaRegularizer', params=[Param(name='n', distribution=IntRangeDistribution(low=1, high=30)), Param(name='SparsePhi', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0)), Param(name='SparseTheta', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0))]), values=[12, 862.6766687279264, 135.15287388864226])], required_params=Stage(stage_type=StageType(name='General', params=[Param(name='basic_topics_count', distribution=IntRangeDistribution(low=0, high=5)), Param(name='ext_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_elem_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_mutation_selector', distribution=FloatRangeDistribution(low=0.0, high=1.0))]), values=[0, 0.6065560125611166, 0.6935414883927496, 0.4825868764489578])), with fitness: 12.126965949662853.ITERATION TIME: 129.09033250808716DATASET __noname__.TOPICS NUM 25.RUN ID ee461a46-d514-43d0-952a-8b6c87bc1818.\n", + "2024-06-09 23:59:25,387 - root - INFO - Sending a best individual to be logged\n", + "2024-06-09 23:59:25,388 - root - INFO - Doing fitness calculating with individual {\"id\":\"5c2c8a77-5695-49f1-afc8-978c7264d5e9\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":{\"avg_coherence_score\":12.126965949662853,\"perplexityScore\":1367.0140380859375,\"backgroundTokensRatioScore\":0.05860655754804611,\"contrast\":0.0,\"purity\":0.0,\"kernelSize\":0.0,\"npmi_50_list\":null,\"npmi_50\":null,\"sparsity_phi\":0.0,\"sparsity_theta\":0.0,\"topic_significance_uni\":null,\"topic_significance_vacuous\":null,\"topic_significance_back\":null,\"switchP_list\":[NaN],\"switchP\":NaN,\"all_topics\":true,\"coherence_10_list\":[6.847273399192251,6.730724307314206,6.81015328161727,6.781480270718103,6.77694276559601,6.415694418173986,6.5402244804936425,6.782087644950563,6.701378569528667,6.856104842127825,6.715258904023474,6.906832410962406,6.805157772835139,6.784559318540944,6.71502212100932,6.917367857924914,6.698414702271158,6.991365593236741,6.723793753535029,6.907165820793221,6.855182938882594,6.705875024615536,6.736505993320824,6.436080993913767,6.685136164271975],\"coherence_10\":6.753031333993983,\"coherence_15_list\":[6.533259130184876,6.7434837491616255,6.676293077333751,6.622572816911698,6.634785696596075,6.524346738566347,6.807546066213145,6.815954094691511,6.616734862340504,6.806680003129368,6.7020103275216725,6.761203755026397,6.717342134701922,6.8652863809880085,6.50350987427352,6.7755456749933485,6.60972623815657,6.706803361581337,6.70538407883765,6.668008457557744,6.787711817480435,6.382209451443663,6.501393967308762,6.636975246871754,6.661356405379554],\"coherence_15\":6.67064493629005,\"coherence_20_list\":[6.543529778298098,6.659106257405972,6.55089693627856,6.601624053428274,6.477956477788523,6.584763982393815,6.656955728438524,6.712728119404426,6.725730382236146,6.699997856014576,6.718095271814978,6.702235053167015,6.847602816557056,6.783694536761621,6.496320847180677,6.8217283570841225,6.573961657039192,6.615320972439311,6.640206956571775,6.635693031269098,6.601603508474884,6.564475729543362,6.402111263533532,6.540205951744872,6.718571003168364],\"coherence_20\":6.635004661121472,\"coherence_25_list\":[6.4562658078034,6.59966394892218,6.630403748877014,6.690951976281171,6.488971781028378,6.577738053891906,6.523056981418214,6.723446755987442,6.718751309089274,6.5988511561993475,6.653573921873519,6.449681069821281,6.749235806281429,6.670130443377854,6.515019948150179,6.644008902225608,6.548021815408342,6.6152028000627165,6.50265717472447,6.585544502416424,6.5788085660430635,6.556676378307134,6.432315960631782,6.482272836867887,6.570576649251297],\"coherence_25\":6.582473131797652,\"coherence_30_list\":[6.498301850613089,6.522535683163357,6.49412486825226,6.572057095606508,6.4021018511757735,6.46322155791618,6.416418018786766,6.612127580417481,6.660997116306298,6.538956654187582,6.5562471519261605,6.430528212033041,6.465225422306231,6.466394285190932,6.441010902849499,6.589092563683,6.598103637604237,6.554074123829485,6.521299828945756,6.4539040677744,6.555482680895484,6.557706911577103,6.423998047441563,6.473138026882254,6.397376493040208],\"coherence_30\":6.506576985296187,\"coherence_35_list\":[6.403993328955538,6.462154149778253,6.440989520026369,6.4165717176204735,6.344841496274747,6.370768144675219,6.324671198303996,6.551281980225318,6.444174891534814,6.417394427334757,6.437859139213485,6.324413395987504,6.374993912044886,6.452615949237499,6.391256217156041,6.5181892514292326,6.419554682954688,6.51480769332043,6.4332619550790024,6.392868815504892,6.450582928822726,6.408463110518769,6.220838899490337,6.448118184151123,6.308714264986353],\"coherence_35\":6.410935170185058,\"coherence_40_list\":[6.30776544475684,6.440888689958534,6.393979992768134,6.297851305062039,6.322423057973425,6.239924453458568,6.3006782655132785,6.4747793056016185,6.3901285235578875,6.431380765162843,6.387165109423467,6.2123813395574,6.338190936249873,6.286209005533212,6.344914954513021,6.428270985096164,6.358408527484597,6.447132442119591,6.364551711901957,6.3073312319138894,6.1900493234735325,6.248089748961348,6.175713956500994,6.387114894051671,6.205720811567557],\"coherence_40\":6.331241791286456,\"coherence_45_list\":[6.196164221994946,6.351691112650757,6.3876871616475634,6.2169367259764,6.2700687095415955,6.154446551697229,6.17751286550516,6.497909083831898,6.350876703135634,6.353290419225084,6.273368257422746,6.10877835770136,6.125628963460158,6.163246233493589,6.285113911098988,6.387130315208957,6.27931548552275,6.413741896156556,6.239117383936755,6.292372700874718,6.092104690588711,6.243802338228963,6.118583431499146,6.301566496512477,6.146092099903227],\"coherence_45\":6.257061844672615,\"coherence_50_list\":[6.148699935315383,6.326911028321904,6.239947269495553,6.184194116344167,6.213987750895649,6.154614045231385,6.101080248667447,6.408587979920304,6.254104246981741,6.249013718990919,6.265822702728159,6.0037499668126015,6.018770607969764,6.1650329870269305,6.180272942662255,6.25422435765407,6.166204569308145,6.334086157926717,6.170494242529895,6.236511466949228,6.050193270336161,6.1273842321012815,5.94613194631003,6.209544392561376,6.111285900779486],\"coherence_50\":6.180834003352823,\"coherence_55_list\":[6.153647478055628,6.28603684260796,6.212023155321504,6.1382169485543345,6.074421697343837,6.104739726572959,6.051968223883241,6.169135553843967,6.195168094416744,6.242748775556229,6.199417846435927,5.9910717059339165,6.025975591178977,6.014461955408583,6.089510694517783,6.102852534309653,6.113577271330549,6.245489116366203,6.099461673251516,6.111546243466477,5.994337079709307,6.072900822653464,5.803431514985174,6.111547412573434,6.055213608917615],\"coherence_55\":6.1063560626878,\"npmi_15\":null,\"npmi_25\":null},\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":9,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:59:25,389 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:59:25,997 - root - INFO - Training is complete\n", + "2024-06-09 23:59:26,136 - root - INFO - Wow! all topics\n", + "2024-06-09 23:59:26,137 - root - INFO - Building dictionary\n", + "2024-06-09 23:59:26,241 - root - INFO - COMPONENTS 6.180834003352823 5.94613194631003\n", + "2024-06-09 23:59:26,460 - root - INFO - Fitness estimation took 1.07\n", + "2024-06-09 23:59:26,681 - root - INFO - Logging params and artifacts to mlflow\n", + "2024-06-09 23:59:26,682 - root - INFO - Created experiment_0\n", + "2024-06-09 23:59:26,701 - root - INFO - Experiment exists, omitting creation\n", + "2024-06-09 23:59:26,701 - root - INFO - Experiment run name: fitness-__noname__-e7165934-bce6-48e3-83ba-cf9ea2807983_tmp_9\n", + "2024-06-09 23:59:26,780 - root - DEBUG - Params dict: {'0_General_basic_topics_count': 0, '0_General_ext_mutation_prob': 0.6065560125611166, '0_General_ext_elem_mutation_prob': 0.6935414883927496, '0_General_ext_mutation_selector': 0.4825868764489578, '1_SparseThetaRegularizer_n': 12, '1_SparseThetaRegularizer_SparsePhi': 862.6766687279264, '1_SparseThetaRegularizer_SparseTheta': 135.15287388864226}\n", + "2024-06-09 23:59:27,237 - root - INFO - Logged params and artifacts to mlflow\n", + "2024-06-09 23:59:27,294 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:59:27,295 - GA_algo - INFO - ENTERING GENERATION 10\n", + "2024-06-09 23:59:27,295 - GA_algo - INFO - PAIRS ARE CREATED\n", + "2024-06-09 23:59:27,308 - root - INFO - Calculating fitness...\n", + "2024-06-09 23:59:27,309 - root - INFO - Doing fitness calculating with individual {\"id\":\"bdeba485-1f62-40b4-a745-609740033c80\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:59:27,310 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:59:28,727 - root - INFO - Training is complete\n", + "2024-06-09 23:59:28,966 - root - INFO - Wow! all topics\n", + "2024-06-09 23:59:28,967 - root - INFO - Building dictionary\n", + "2024-06-09 23:59:29,176 - root - INFO - COMPONENTS 6.169403230192717 5.885853870558686\n", + "2024-06-09 23:59:29,492 - root - INFO - Fitness estimation took 2.18\n", + "2024-06-09 23:59:29,821 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:59:29,822 - root - INFO - Doing fitness calculating with individual {\"id\":\"9255bbbc-fefb-4548-8e14-6756d4c6698f\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.20382144321324902,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:59:29,823 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:59:32,334 - root - INFO - Training is complete\n", + "2024-06-09 23:59:32,702 - root - INFO - Wow! all topics\n", + "2024-06-09 23:59:32,702 - root - INFO - Building dictionary\n", + "2024-06-09 23:59:33,058 - root - INFO - COMPONENTS 6.180889957727971 5.885853870558686\n", + "2024-06-09 23:59:33,520 - root - INFO - Fitness estimation took 3.70\n", + "2024-06-09 23:59:33,893 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:59:33,894 - root - INFO - Doing fitness calculating with individual {\"id\":\"11d4e694-cf13-4385-b510-398a00dd4628\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.6065560125611166,0.8793124625020681,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:59:33,895 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:59:37,708 - root - INFO - Training is complete\n", + "2024-06-09 23:59:38,285 - root - INFO - Wow! all topics\n", + "2024-06-09 23:59:38,287 - root - INFO - Building dictionary\n", + "2024-06-09 23:59:38,848 - root - INFO - COMPONENTS 6.187366529457325 5.8981057732722135\n", + "2024-06-09 23:59:39,492 - root - INFO - Fitness estimation took 5.60\n", + "2024-06-09 23:59:39,924 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:59:39,926 - root - INFO - Doing fitness calculating with individual {\"id\":\"df4b4746-6d84-47e5-afb4-d4fc6c9530ee\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.053890396724473266,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:59:39,926 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:59:45,314 - root - INFO - Training is complete\n", + "2024-06-09 23:59:46,107 - root - INFO - Wow! all topics\n", + "2024-06-09 23:59:46,108 - root - INFO - Building dictionary\n", + "2024-06-09 23:59:46,894 - root - INFO - COMPONENTS 6.099958173621709 4.942882704639126\n", + "2024-06-09 23:59:47,765 - root - INFO - Fitness estimation took 7.84\n", + "2024-06-09 23:59:48,272 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:59:48,273 - root - INFO - Doing fitness calculating with individual {\"id\":\"ba963a7e-4e91-4f32-869f-44d98ed2c68c\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:59:48,274 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:59:49,694 - root - INFO - Training is complete\n", + "2024-06-09 23:59:49,934 - root - INFO - Wow! all topics\n", + "2024-06-09 23:59:49,935 - root - INFO - Building dictionary\n", + "2024-06-09 23:59:50,146 - root - INFO - COMPONENTS 6.169403230192717 5.885853870558686\n", + "2024-06-09 23:59:50,464 - root - INFO - Fitness estimation took 2.19\n", + "2024-06-09 23:59:50,787 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:59:50,788 - root - INFO - Doing fitness calculating with individual {\"id\":\"d234fa3a-f7ce-455a-a022-a13fc53a66f6\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.08316206321031394,0.46738007747537214,0.8622486657466205]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:59:50,789 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-09 23:59:55,724 - root - INFO - Training is complete\n", + "2024-06-09 23:59:56,440 - root - INFO - Wow! all topics\n", + "2024-06-09 23:59:56,441 - root - INFO - Building dictionary\n", + "2024-06-09 23:59:57,127 - root - INFO - COMPONENTS 6.154888492478811 5.636303991935876\n", + "2024-06-09 23:59:57,908 - root - INFO - Fitness estimation took 7.12\n", + "2024-06-09 23:59:58,383 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-09 23:59:58,385 - root - INFO - Doing fitness calculating with individual {\"id\":\"4b0f114a-dcc2-437e-8c14-7bd11c65a5b3\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[5,0.20382144321324902,0.045754488640769475,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-09 23:59:58,385 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:00:00,178 - root - INFO - Training is complete\n", + "2024-06-10 00:00:00,479 - root - INFO - Wow! all topics\n", + "2024-06-10 00:00:00,480 - root - INFO - Building dictionary\n", + "2024-06-10 00:00:00,761 - root - INFO - COMPONENTS 6.177182770721674 5.8981057732722135\n", + "2024-06-10 00:00:01,157 - root - INFO - Fitness estimation took 2.77\n", + "2024-06-10 00:00:01,525 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:00:01,526 - root - INFO - Doing fitness calculating with individual {\"id\":\"1741540c-081b-4e52-b1bc-09b9b472c6a4\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[16,-208.08637371442603,429.1129407050603]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[14,-580.3569019472527,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:00:01,527 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:00:02,937 - root - INFO - Training is complete\n", + "2024-06-10 00:00:03,101 - root - INFO - Building dictionary\n", + "2024-06-10 00:00:03,210 - root - INFO - COMPONENTS 0.0 0\n", + "2024-06-10 00:00:03,310 - root - INFO - Fitness estimation took 1.78\n", + "2024-06-10 00:00:03,493 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:00:03,494 - root - INFO - Doing fitness calculating with individual {\"id\":\"d632530f-8d76-4eae-b1f1-9890ccaeb81a\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.5987960491423391,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:00:03,495 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:00:04,739 - root - INFO - Training is complete\n", + "2024-06-10 00:00:04,955 - root - INFO - Wow! all topics\n", + "2024-06-10 00:00:04,956 - root - INFO - Building dictionary\n", + "2024-06-10 00:00:05,142 - root - INFO - COMPONENTS 6.181877012179996 5.854526196544299\n", + "2024-06-10 00:00:05,435 - root - INFO - Fitness estimation took 1.94\n", + "2024-06-10 00:00:05,747 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:00:05,748 - root - INFO - Doing fitness calculating with individual {\"id\":\"180329d1-c9a1-4053-b1d8-acfbc6f46c71\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.053890396724473266,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:00:05,749 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:00:09,771 - root - INFO - Training is complete\n", + "2024-06-10 00:00:10,382 - root - INFO - Wow! all topics\n", + "2024-06-10 00:00:10,383 - root - INFO - Building dictionary\n", + "2024-06-10 00:00:10,979 - root - INFO - COMPONENTS 6.180789372910162 5.8736574800087595\n", + "2024-06-10 00:00:11,654 - root - INFO - Fitness estimation took 5.91\n", + "2024-06-10 00:00:12,093 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:00:12,094 - root - INFO - Doing fitness calculating with individual {\"id\":\"3de7bdc4-d062-4a66-9ebd-859630bc49eb\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.20382144321324902,0.46738007747537214,0.7238629361718627]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:00:12,094 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:00:14,908 - root - INFO - Training is complete\n", + "2024-06-10 00:00:15,338 - root - INFO - Wow! all topics\n", + "2024-06-10 00:00:15,339 - root - INFO - Building dictionary\n", + "2024-06-10 00:00:15,751 - root - INFO - COMPONENTS 6.1814880221685735 5.8981057732722135\n", + "2024-06-10 00:00:16,260 - root - INFO - Fitness estimation took 4.17\n", + "2024-06-10 00:00:16,646 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:00:16,647 - root - INFO - Doing fitness calculating with individual {\"id\":\"881b7f5f-927e-4167-bae9-2989db31a4c1\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.8066675211580605,0.8793124625020681,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:00:16,648 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:00:20,452 - root - INFO - Training is complete\n", + "2024-06-10 00:00:21,006 - root - INFO - Wow! all topics\n", + "2024-06-10 00:00:21,007 - root - INFO - Building dictionary\n", + "2024-06-10 00:00:21,540 - root - INFO - COMPONENTS 6.187366529457325 5.8981057732722135\n", + "2024-06-10 00:00:22,170 - root - INFO - Fitness estimation took 5.52\n", + "2024-06-10 00:00:22,596 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:00:22,597 - root - INFO - Doing fitness calculating with individual {\"id\":\"87328443-4471-44f4-ba82-4452a2b97420\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:00:22,598 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:00:26,333 - root - INFO - Training is complete\n", + "2024-06-10 00:00:26,864 - root - INFO - Wow! all topics\n", + "2024-06-10 00:00:26,865 - root - INFO - Building dictionary\n", + "2024-06-10 00:00:27,362 - root - INFO - COMPONENTS 6.156345636851698 5.570789303948351\n", + "2024-06-10 00:00:27,975 - root - INFO - Fitness estimation took 5.38\n", + "2024-06-10 00:00:28,384 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:00:28,385 - root - INFO - Doing fitness calculating with individual {\"id\":\"218ad24a-0635-4ce1-9d98-aa2c4139b526\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:00:28,386 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:00:32,419 - root - INFO - Training is complete\n", + "2024-06-10 00:00:33,030 - root - INFO - Wow! all topics\n", + "2024-06-10 00:00:33,031 - root - INFO - Building dictionary\n", + "2024-06-10 00:00:33,623 - root - INFO - COMPONENTS 6.181130914156617 5.8736574800087595\n", + "2024-06-10 00:00:34,303 - root - INFO - Fitness estimation took 5.92\n", + "2024-06-10 00:00:34,749 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:00:34,751 - root - INFO - Doing fitness calculating with individual {\"id\":\"918ed1b9-79b8-4d14-b0a2-b223f71bcaac\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[10,-334.3018253454877,503.0033770985847]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[29,868.2703427609019,2.2980766899298715]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.08316206321031394,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:00:34,751 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:00:38,392 - root - INFO - Training is complete\n", + "2024-06-10 00:00:38,893 - root - INFO - Wow! all topics\n", + "2024-06-10 00:00:38,894 - root - INFO - Building dictionary\n", + "2024-06-10 00:00:39,382 - root - INFO - COMPONENTS 6.148065048541038 5.535896956942034\n", + "2024-06-10 00:00:39,968 - root - INFO - Fitness estimation took 5.22\n", + "2024-06-10 00:00:40,376 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:00:40,377 - root - INFO - Doing fitness calculating with individual {\"id\":\"2f319127-3a0a-4e29-8fda-04e5d41d7447\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:00:40,378 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:00:43,228 - root - INFO - Training is complete\n", + "2024-06-10 00:00:43,649 - root - INFO - Wow! all topics\n", + "2024-06-10 00:00:43,650 - root - INFO - Building dictionary\n", + "2024-06-10 00:00:44,044 - root - INFO - COMPONENTS 6.1814880221685735 5.8981057732722135\n", + "2024-06-10 00:00:44,542 - root - INFO - Fitness estimation took 4.16\n", + "2024-06-10 00:00:44,929 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:00:44,930 - root - INFO - Doing fitness calculating with individual {\"id\":\"1370c27e-ebcc-4a41-991e-a19184723c34\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.053890396724473266,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:00:44,930 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:00:48,984 - root - INFO - Training is complete\n", + "2024-06-10 00:00:49,607 - root - INFO - Wow! all topics\n", + "2024-06-10 00:00:49,608 - root - INFO - Building dictionary\n", + "2024-06-10 00:00:50,194 - root - INFO - COMPONENTS 6.180789372910162 5.8736574800087595\n", + "2024-06-10 00:00:50,889 - root - INFO - Fitness estimation took 5.96\n", + "2024-06-10 00:00:51,341 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:00:51,342 - root - INFO - Doing fitness calculating with individual {\"id\":\"7eed15d9-7089-41fd-8d28-0bf1ab6d0cdd\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:00:51,343 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:00:54,771 - root - INFO - Training is complete\n", + "2024-06-10 00:00:55,270 - root - INFO - Wow! all topics\n", + "2024-06-10 00:00:55,271 - root - INFO - Building dictionary\n", + "2024-06-10 00:00:55,769 - root - INFO - COMPONENTS 6.188957533238761 5.917344732418264\n", + "2024-06-10 00:00:56,351 - root - INFO - Fitness estimation took 5.01\n", + "2024-06-10 00:00:56,766 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:00:56,767 - root - INFO - Doing fitness calculating with individual {\"id\":\"4eb6af3c-7194-4604-9b06-7876d482ae81\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:00:56,768 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:01:00,191 - root - INFO - Training is complete\n", + "2024-06-10 00:01:00,693 - root - INFO - Wow! all topics\n", + "2024-06-10 00:01:00,694 - root - INFO - Building dictionary\n", + "2024-06-10 00:01:01,172 - root - INFO - COMPONENTS 6.188957533238761 5.917344732418264\n", + "2024-06-10 00:01:01,751 - root - INFO - Fitness estimation took 4.98\n", + "2024-06-10 00:01:02,160 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:01:02,161 - root - INFO - The fitness results have been obtained\n", + "2024-06-10 00:01:02,162 - GA_algo - INFO - size of the new generation is 19\n", + "2024-06-10 00:01:02,163 - GA_algo - INFO - CROSSOVER IS OVER\n", + "2024-06-10 00:01:02,464 - root - INFO - Calculating fitness...\n", + "2024-06-10 00:01:02,465 - root - INFO - Doing fitness calculating with individual {\"id\":\"ce1722d6-494f-4a2b-be58-5487227936aa\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.8793124625020681,0.30481282306567203]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:01:02,466 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:01:06,158 - root - INFO - Training is complete\n", + "2024-06-10 00:01:06,671 - root - INFO - Wow! all topics\n", + "2024-06-10 00:01:06,672 - root - INFO - Building dictionary\n", + "2024-06-10 00:01:07,174 - root - INFO - COMPONENTS 6.156345636851698 5.570789303948351\n", + "2024-06-10 00:01:07,766 - root - INFO - Fitness estimation took 5.30\n", + "2024-06-10 00:01:08,173 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:01:08,174 - root - INFO - Doing fitness calculating with individual {\"id\":\"56e47956-c74b-4ece-bb7f-7ce8586c75ae\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,-450.6068772959519,-916.210057776243]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.8066675211580605,0.8793124625020681,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":10,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:01:08,175 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:01:11,954 - root - INFO - Training is complete\n", + "2024-06-10 00:01:12,129 - root - INFO - Building dictionary\n", + "2024-06-10 00:01:12,256 - root - INFO - COMPONENTS 0.0 0\n", + "2024-06-10 00:01:12,363 - root - INFO - Fitness estimation took 4.19\n", + "2024-06-10 00:01:12,572 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:01:12,573 - root - INFO - The fitness results have been obtained\n", + "2024-06-10 00:01:12,573 - GA_algo - INFO - MUTATION IS OVER\n", + "2024-06-10 00:01:12,574 - GA_algo - INFO - Population len 11. Best params so far: pipeline=Pipeline(stages=[Stage(stage_type=StageType(name='SparseThetaRegularizer', params=[Param(name='n', distribution=IntRangeDistribution(low=1, high=30)), Param(name='SparsePhi', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0)), Param(name='SparseTheta', distribution=FloatRangeDistribution(low=-1000.0, high=1000.0))]), values=[12, 862.6766687279264, 135.15287388864226])], required_params=Stage(stage_type=StageType(name='General', params=[Param(name='basic_topics_count', distribution=IntRangeDistribution(low=0, high=5)), Param(name='ext_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_elem_mutation_prob', distribution=FloatRangeDistribution(low=0.0, high=1.0)), Param(name='ext_mutation_selector', distribution=FloatRangeDistribution(low=0.0, high=1.0))]), values=[0, 0.6065560125611166, 0.6935414883927496, 0.4825868764489578])), with fitness: 12.126965949662853.ITERATION TIME: 105.27944612503052DATASET __noname__.TOPICS NUM 25.RUN ID ee461a46-d514-43d0-952a-8b6c87bc1818.\n", + "2024-06-10 00:01:12,575 - root - INFO - Sending a best individual to be logged\n", + "2024-06-10 00:01:12,576 - root - INFO - Doing fitness calculating with individual {\"id\":\"5c2c8a77-5695-49f1-afc8-978c7264d5e9\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":{\"avg_coherence_score\":12.126965949662853,\"perplexityScore\":1367.0140380859375,\"backgroundTokensRatioScore\":0.05860655754804611,\"contrast\":0.0,\"purity\":0.0,\"kernelSize\":0.0,\"npmi_50_list\":null,\"npmi_50\":null,\"sparsity_phi\":0.0,\"sparsity_theta\":0.0,\"topic_significance_uni\":null,\"topic_significance_vacuous\":null,\"topic_significance_back\":null,\"switchP_list\":[NaN],\"switchP\":NaN,\"all_topics\":true,\"coherence_10_list\":[6.847273399192251,6.730724307314206,6.81015328161727,6.781480270718103,6.77694276559601,6.415694418173986,6.5402244804936425,6.782087644950563,6.701378569528667,6.856104842127825,6.715258904023474,6.906832410962406,6.805157772835139,6.784559318540944,6.71502212100932,6.917367857924914,6.698414702271158,6.991365593236741,6.723793753535029,6.907165820793221,6.855182938882594,6.705875024615536,6.736505993320824,6.436080993913767,6.685136164271975],\"coherence_10\":6.753031333993983,\"coherence_15_list\":[6.533259130184876,6.7434837491616255,6.676293077333751,6.622572816911698,6.634785696596075,6.524346738566347,6.807546066213145,6.815954094691511,6.616734862340504,6.806680003129368,6.7020103275216725,6.761203755026397,6.717342134701922,6.8652863809880085,6.50350987427352,6.7755456749933485,6.60972623815657,6.706803361581337,6.70538407883765,6.668008457557744,6.787711817480435,6.382209451443663,6.501393967308762,6.636975246871754,6.661356405379554],\"coherence_15\":6.67064493629005,\"coherence_20_list\":[6.543529778298098,6.659106257405972,6.55089693627856,6.601624053428274,6.477956477788523,6.584763982393815,6.656955728438524,6.712728119404426,6.725730382236146,6.699997856014576,6.718095271814978,6.702235053167015,6.847602816557056,6.783694536761621,6.496320847180677,6.8217283570841225,6.573961657039192,6.615320972439311,6.640206956571775,6.635693031269098,6.601603508474884,6.564475729543362,6.402111263533532,6.540205951744872,6.718571003168364],\"coherence_20\":6.635004661121472,\"coherence_25_list\":[6.4562658078034,6.59966394892218,6.630403748877014,6.690951976281171,6.488971781028378,6.577738053891906,6.523056981418214,6.723446755987442,6.718751309089274,6.5988511561993475,6.653573921873519,6.449681069821281,6.749235806281429,6.670130443377854,6.515019948150179,6.644008902225608,6.548021815408342,6.6152028000627165,6.50265717472447,6.585544502416424,6.5788085660430635,6.556676378307134,6.432315960631782,6.482272836867887,6.570576649251297],\"coherence_25\":6.582473131797652,\"coherence_30_list\":[6.498301850613089,6.522535683163357,6.49412486825226,6.572057095606508,6.4021018511757735,6.46322155791618,6.416418018786766,6.612127580417481,6.660997116306298,6.538956654187582,6.5562471519261605,6.430528212033041,6.465225422306231,6.466394285190932,6.441010902849499,6.589092563683,6.598103637604237,6.554074123829485,6.521299828945756,6.4539040677744,6.555482680895484,6.557706911577103,6.423998047441563,6.473138026882254,6.397376493040208],\"coherence_30\":6.506576985296187,\"coherence_35_list\":[6.403993328955538,6.462154149778253,6.440989520026369,6.4165717176204735,6.344841496274747,6.370768144675219,6.324671198303996,6.551281980225318,6.444174891534814,6.417394427334757,6.437859139213485,6.324413395987504,6.374993912044886,6.452615949237499,6.391256217156041,6.5181892514292326,6.419554682954688,6.51480769332043,6.4332619550790024,6.392868815504892,6.450582928822726,6.408463110518769,6.220838899490337,6.448118184151123,6.308714264986353],\"coherence_35\":6.410935170185058,\"coherence_40_list\":[6.30776544475684,6.440888689958534,6.393979992768134,6.297851305062039,6.322423057973425,6.239924453458568,6.3006782655132785,6.4747793056016185,6.3901285235578875,6.431380765162843,6.387165109423467,6.2123813395574,6.338190936249873,6.286209005533212,6.344914954513021,6.428270985096164,6.358408527484597,6.447132442119591,6.364551711901957,6.3073312319138894,6.1900493234735325,6.248089748961348,6.175713956500994,6.387114894051671,6.20572081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+ "2024-06-10 00:01:12,576 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:01:13,174 - root - INFO - Training is complete\n", + "2024-06-10 00:01:13,313 - root - INFO - Wow! all topics\n", + "2024-06-10 00:01:13,313 - root - INFO - Building dictionary\n", + "2024-06-10 00:01:13,417 - root - INFO - COMPONENTS 6.180834003352823 5.94613194631003\n", + "2024-06-10 00:01:13,635 - root - INFO - Fitness estimation took 1.06\n", + "2024-06-10 00:01:13,855 - root - INFO - Logging params and artifacts to mlflow\n", + "2024-06-10 00:01:13,855 - root - INFO - Created experiment_0\n", + "2024-06-10 00:01:13,873 - root - INFO - Experiment exists, omitting creation\n", + "2024-06-10 00:01:13,874 - root - INFO - Experiment run name: fitness-__noname__-c670fcfc-8380-4daa-b9ec-228f3d5cb784_tmp_10\n", + "2024-06-10 00:01:13,946 - root - DEBUG - Params dict: {'0_General_basic_topics_count': 0, '0_General_ext_mutation_prob': 0.6065560125611166, '0_General_ext_elem_mutation_prob': 0.6935414883927496, '0_General_ext_mutation_selector': 0.4825868764489578, '1_SparseThetaRegularizer_n': 12, '1_SparseThetaRegularizer_SparsePhi': 862.6766687279264, '1_SparseThetaRegularizer_SparseTheta': 135.15287388864226}\n", + "2024-06-10 00:01:14,473 - root - INFO - Logged params and artifacts to mlflow\n", + "2024-06-10 00:01:14,525 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:01:14,526 - GA_algo - INFO - ENTERING GENERATION 11\n", + "2024-06-10 00:01:14,527 - GA_algo - INFO - PAIRS ARE CREATED\n", + "2024-06-10 00:01:14,550 - root - INFO - Calculating fitness...\n", + "2024-06-10 00:01:14,551 - root - INFO - Doing fitness calculating with individual {\"id\":\"f0cb8cc9-c044-4cbd-8232-50d144df0a79\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:01:14,552 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:01:16,577 - root - INFO - Training is complete\n", + "2024-06-10 00:01:16,890 - root - INFO - Wow! all topics\n", + "2024-06-10 00:01:16,891 - root - INFO - Building dictionary\n", + "2024-06-10 00:01:17,173 - root - INFO - COMPONENTS 6.177241647042988 5.885853870558686\n", + "2024-06-10 00:01:17,562 - root - INFO - Fitness estimation took 3.01\n", + "2024-06-10 00:01:17,912 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:01:17,913 - root - INFO - Doing fitness calculating with individual {\"id\":\"4c0712e5-7a04-4343-ab4f-4cb78215111c\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:01:17,914 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:01:19,847 - root - INFO - Training is complete\n", + "2024-06-10 00:01:20,141 - root - INFO - Wow! all topics\n", + "2024-06-10 00:01:20,142 - root - INFO - Building dictionary\n", + "2024-06-10 00:01:20,408 - root - INFO - COMPONENTS 6.167701085044618 5.854526196544299\n", + "2024-06-10 00:01:20,784 - root - INFO - Fitness estimation took 2.87\n", + "2024-06-10 00:01:21,116 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:01:21,117 - root - INFO - Doing fitness calculating with individual {\"id\":\"68960ed2-7772-4424-bcd9-8cb1de10dfd9\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.053890396724473266,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:01:21,118 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:01:22,290 - root - INFO - Training is complete\n", + "2024-06-10 00:01:22,503 - root - INFO - Wow! all topics\n", + "2024-06-10 00:01:22,504 - root - INFO - Building dictionary\n", + "2024-06-10 00:01:22,680 - root - INFO - COMPONENTS 6.181608210338693 5.8523015349710885\n", + "2024-06-10 00:01:22,960 - root - INFO - Fitness estimation took 1.84\n", + "2024-06-10 00:01:23,256 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:01:23,257 - root - INFO - Doing fitness calculating with individual {\"id\":\"b374e9b2-9d97-4ecc-bd5a-8ac92b22670c\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.6065560125611166,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:01:23,258 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:01:26,103 - root - INFO - Training is complete\n", + "2024-06-10 00:01:26,542 - root - INFO - Wow! all topics\n", + "2024-06-10 00:01:26,543 - root - INFO - Building dictionary\n", + "2024-06-10 00:01:26,958 - root - INFO - COMPONENTS 6.1814880221685735 5.8981057732722135\n", + "2024-06-10 00:01:27,471 - root - INFO - Fitness estimation took 4.21\n", + "2024-06-10 00:01:27,866 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:01:27,867 - root - INFO - Doing fitness calculating with individual {\"id\":\"e95492d5-59ee-4fa6-8895-5d4e1cf3378b\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.053890396724473266,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:01:27,868 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:01:31,892 - root - INFO - Training is complete\n", + "2024-06-10 00:01:32,474 - root - INFO - Wow! all topics\n", + "2024-06-10 00:01:32,475 - root - INFO - Building dictionary\n", + "2024-06-10 00:01:33,034 - root - INFO - COMPONENTS 6.181756063843047 5.8736574800087595\n", + "2024-06-10 00:01:33,691 - root - INFO - Fitness estimation took 5.82\n", + "2024-06-10 00:01:34,123 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:01:34,124 - root - INFO - Doing fitness calculating with individual {\"id\":\"d52588fe-a244-48d4-ae97-1cfd5df24f39\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:01:34,125 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:01:36,946 - root - INFO - Training is complete\n", + "2024-06-10 00:01:37,386 - root - INFO - Wow! all topics\n", + "2024-06-10 00:01:37,388 - root - INFO - Building dictionary\n", + "2024-06-10 00:01:37,817 - root - INFO - COMPONENTS 6.1814880221685735 5.8981057732722135\n", + "2024-06-10 00:01:38,333 - root - INFO - Fitness estimation took 4.21\n", + "2024-06-10 00:01:38,729 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:01:38,730 - root - INFO - Doing fitness calculating with individual {\"id\":\"73c64fac-53f6-44d9-b234-5b74a667c563\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.8793124625020681,0.30481282306567203]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:01:38,730 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:01:39,906 - root - INFO - Training is complete\n", + "2024-06-10 00:01:40,110 - root - INFO - Wow! all topics\n", + "2024-06-10 00:01:40,112 - root - INFO - Building dictionary\n", + "2024-06-10 00:01:40,283 - root - INFO - COMPONENTS 6.181608210338693 5.8523015349710885\n", + "2024-06-10 00:01:40,560 - root - INFO - Fitness estimation took 1.83\n", + "2024-06-10 00:01:40,868 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:01:40,870 - root - INFO - Doing fitness calculating with individual {\"id\":\"66bbd212-c97c-42be-81cf-0834c4c2b2ea\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:01:40,870 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:01:44,101 - root - INFO - Training is complete\n", + "2024-06-10 00:01:44,553 - root - INFO - Wow! all topics\n", + "2024-06-10 00:01:44,554 - root - INFO - Building dictionary\n", + "2024-06-10 00:01:44,970 - root - INFO - COMPONENTS 6.165518947300975 5.727294048279636\n", + "2024-06-10 00:01:45,487 - root - INFO - Fitness estimation took 4.62\n", + "2024-06-10 00:01:45,867 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:01:45,868 - root - INFO - Doing fitness calculating with individual {\"id\":\"50825caa-d648-41f6-b5e4-df4570dfb83e\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.6935414883927496,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:01:45,869 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:01:49,893 - root - INFO - Training is complete\n", + "2024-06-10 00:01:50,486 - root - INFO - Wow! all topics\n", + "2024-06-10 00:01:50,487 - root - INFO - Building dictionary\n", + "2024-06-10 00:01:51,066 - root - INFO - COMPONENTS 6.181756063843047 5.8736574800087595\n", + "2024-06-10 00:01:51,734 - root - INFO - Fitness estimation took 5.87\n", + "2024-06-10 00:01:52,170 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:01:52,171 - root - INFO - Doing fitness calculating with individual {\"id\":\"066aedd9-7235-4f33-9593-9397a57db9ea\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.8793124625020681,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:01:52,172 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:01:54,799 - root - INFO - Training is complete\n", + "2024-06-10 00:01:55,192 - root - INFO - Wow! all topics\n", + "2024-06-10 00:01:55,193 - root - INFO - Building dictionary\n", + "2024-06-10 00:01:55,564 - root - INFO - COMPONENTS 6.18095395500894 5.8981057732722135\n", + "2024-06-10 00:01:56,036 - root - INFO - Fitness estimation took 3.86\n", + "2024-06-10 00:01:56,405 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:01:56,406 - root - INFO - Doing fitness calculating with individual {\"id\":\"2475fa63-3d4d-41cf-9d31-badb0cf5f9d5\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.20382144321324902,0.46738007747537214,0.30481282306567203]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:01:56,407 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:02:00,869 - root - INFO - Training is complete\n", + "2024-06-10 00:02:01,472 - root - INFO - Wow! all topics\n", + "2024-06-10 00:02:01,473 - root - INFO - Building dictionary\n", + "2024-06-10 00:02:02,079 - root - INFO - COMPONENTS 6.145978346089301 5.492819122087649\n", + "2024-06-10 00:02:02,781 - root - INFO - Fitness estimation took 6.37\n", + "2024-06-10 00:02:03,237 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:02:03,238 - root - INFO - Doing fitness calculating with individual {\"id\":\"e5e909d5-4a45-4547-b603-6af89504a4e8\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.053890396724473266,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:02:03,238 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:02:05,196 - root - INFO - Training is complete\n", + "2024-06-10 00:02:05,506 - root - INFO - Wow! all topics\n", + "2024-06-10 00:02:05,507 - root - INFO - Building dictionary\n", + "2024-06-10 00:02:05,778 - root - INFO - COMPONENTS 6.167701085044618 5.854526196544299\n", + "2024-06-10 00:02:06,151 - root - INFO - Fitness estimation took 2.91\n", + "2024-06-10 00:02:06,495 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:02:06,497 - root - INFO - Doing fitness calculating with individual {\"id\":\"223ecdd6-d49a-4143-aa2c-b45a6ead25be\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.6065560125611166,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:02:06,497 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:02:08,531 - root - INFO - Training is complete\n", + "2024-06-10 00:02:08,862 - root - INFO - Wow! all topics\n", + "2024-06-10 00:02:08,862 - root - INFO - Building dictionary\n", + "2024-06-10 00:02:09,158 - root - INFO - COMPONENTS 6.177241647042988 5.885853870558686\n", + "2024-06-10 00:02:09,557 - root - INFO - Fitness estimation took 3.06\n", + "2024-06-10 00:02:09,913 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:02:09,914 - root - INFO - Doing fitness calculating with individual {\"id\":\"98b79256-019a-4690-8e9d-b46fd87532ab\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[0,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:02:09,915 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:02:11,092 - root - INFO - Training is complete\n", + "2024-06-10 00:02:11,297 - root - INFO - Wow! all topics\n", + "2024-06-10 00:02:11,298 - root - INFO - Building dictionary\n", + "2024-06-10 00:02:11,469 - root - INFO - COMPONENTS 6.181608210338693 5.8523015349710885\n", + "2024-06-10 00:02:11,754 - root - INFO - Fitness estimation took 1.84\n", + "2024-06-10 00:02:12,055 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:02:12,056 - root - INFO - Doing fitness calculating with individual {\"id\":\"245d9a4b-691e-4a8a-8cdb-2685eb3321d2\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,-450.6068772959519,-916.210057776243]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.8066675211580605,0.8793124625020681,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:02:12,057 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:02:15,313 - root - INFO - Training is complete\n", + "2024-06-10 00:02:15,484 - root - INFO - Building dictionary\n", + "2024-06-10 00:02:15,600 - root - INFO - COMPONENTS 0.0 0\n", + "2024-06-10 00:02:15,701 - root - INFO - Fitness estimation took 3.64\n", + "2024-06-10 00:02:15,911 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:02:15,912 - root - INFO - Doing fitness calculating with individual {\"id\":\"9993c8fd-4715-4694-922c-b723588ed18b\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:02:15,913 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:02:17,944 - root - INFO - Training is complete\n", + "2024-06-10 00:02:18,264 - root - INFO - Wow! all topics\n", + "2024-06-10 00:02:18,265 - root - INFO - Building dictionary\n", + "2024-06-10 00:02:18,568 - root - INFO - COMPONENTS 6.177241647042988 5.885853870558686\n", + "2024-06-10 00:02:18,962 - root - INFO - Fitness estimation took 3.05\n", + "2024-06-10 00:02:19,305 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:02:19,306 - root - INFO - Doing fitness calculating with individual {\"id\":\"94b16f1a-df9a-4604-b046-3fd82f28855e\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[3,0.053890396724473266,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:02:19,307 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:02:24,138 - root - INFO - Training is complete\n", + "2024-06-10 00:02:24,867 - root - INFO - Wow! all topics\n", + "2024-06-10 00:02:24,868 - root - INFO - Building dictionary\n", + "2024-06-10 00:02:25,562 - root - INFO - COMPONENTS 6.133514802718029 5.3618500109255685\n", + "2024-06-10 00:02:26,359 - root - INFO - Fitness estimation took 7.05\n", + "2024-06-10 00:02:26,848 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:02:26,850 - root - INFO - Doing fitness calculating with individual {\"id\":\"66d1c384-700b-4470-bba0-55a59d186403\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[6,-450.6068772959519,-916.210057776243]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:02:26,850 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:02:31,874 - root - INFO - Training is complete\n", + "2024-06-10 00:02:32,229 - root - INFO - Building dictionary\n", + "2024-06-10 00:02:32,531 - root - INFO - COMPONENTS 0.0 0\n", + "2024-06-10 00:02:32,815 - root - INFO - Fitness estimation took 5.96\n", + "2024-06-10 00:02:33,083 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:02:33,084 - root - INFO - Doing fitness calculating with individual {\"id\":\"5a75f410-68fe-46a0-984a-da0d7d7d7edb\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.8066675211580605,0.8793124625020681,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:02:33,085 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:02:35,123 - root - INFO - Training is complete\n", + "2024-06-10 00:02:35,439 - root - INFO - Wow! all topics\n", + "2024-06-10 00:02:35,441 - root - INFO - Building dictionary\n", + "2024-06-10 00:02:35,738 - root - INFO - COMPONENTS 6.177241647042988 5.885853870558686\n", + "2024-06-10 00:02:36,128 - root - INFO - Fitness estimation took 3.04\n", + "2024-06-10 00:02:36,470 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:02:36,471 - root - INFO - Doing fitness calculating with individual {\"id\":\"fc50974e-9fce-43ed-a111-803321ed76ae\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:02:36,472 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:02:37,890 - root - INFO - Training is complete\n", + "2024-06-10 00:02:38,127 - root - INFO - Wow! all topics\n", + "2024-06-10 00:02:38,128 - root - INFO - Building dictionary\n", + "2024-06-10 00:02:38,338 - root - INFO - COMPONENTS 6.169403230192717 5.885853870558686\n", + "2024-06-10 00:02:38,658 - root - INFO - Fitness estimation took 2.19\n", + "2024-06-10 00:02:38,987 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:02:38,988 - root - INFO - Doing fitness calculating with individual {\"id\":\"34a3b4fe-35c6-4759-b83f-91e542efe41f\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.20382144321324902,0.46738007747537214,0.7486390329860069]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:02:38,989 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n", + "2024-06-10 00:02:44,481 - root - INFO - Training is complete\n", + "2024-06-10 00:02:45,240 - root - INFO - Wow! all topics\n", + "2024-06-10 00:02:45,241 - root - INFO - Building dictionary\n", + "2024-06-10 00:02:46,000 - root - INFO - COMPONENTS 6.099958173621709 4.942882704639126\n", + "2024-06-10 00:02:46,849 - root - INFO - Fitness estimation took 7.86\n", + "2024-06-10 00:02:47,360 - root - INFO - Deleting bigartm logs: []\n", + "2024-06-10 00:02:47,361 - root - INFO - Doing fitness calculating with individual {\"id\":\"d49c575d-b886-4a2f-b9c7-f70bc1814b04\",\"data_path\":\"tmp/01cefc7c-1438-4248-8789-9aeb6997bba7\",\"params\":{\"pipeline\":{\"stages\":[{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[28,141.03533054556738,395.82369455306207]},{\"stage_type\":{\"name\":\"SparseThetaRegularizer\",\"params\":[{\"name\":\"n\",\"distribution\":{\"low\":1,\"high\":30}},{\"name\":\"SparsePhi\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}},{\"name\":\"SparseTheta\",\"distribution\":{\"low\":-1000.0,\"high\":1000.0}}]},\"values\":[12,862.6766687279264,135.15287388864226]}],\"required_params\":{\"stage_type\":{\"name\":\"General\",\"params\":[{\"name\":\"basic_topics_count\",\"distribution\":{\"low\":0,\"high\":5}},{\"name\":\"ext_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_elem_mutation_prob\",\"distribution\":{\"low\":0.0,\"high\":1.0}},{\"name\":\"ext_mutation_selector\",\"distribution\":{\"low\":0.0,\"high\":1.0}}]},\"values\":[2,0.6065560125611166,0.6935414883927496,0.4825868764489578]}}},\"fitness_name\":\"regular\",\"dataset\":\"__noname__\",\"force_dataset_settings_checkout\":false,\"fitness_value\":null,\"exp_id\":0,\"alg_id\":\"ga\",\"tag\":\"v0\",\"iteration_id\":11,\"topic_count\":25,\"train_option\":\"offline\"}\n", + "2024-06-10 00:02:47,362 - root - INFO - Using TM model: according to fitness name: regular, topics count: 25\n" + ] + } + ], + "source": [ + "mixtures = autotm.fit_predict(pd_dataset.sample(1000)) # we will do the modeling on 1000 random examples from ACL-23 dataset" + ] + }, + { + "cell_type": "markdown", + "id": "e57e1449-cf14-47ca-9610-7675fdc13b6d", + "metadata": {}, + "source": [ + "Now we are going to look at resulting topics. We defined 25 topics, so they can be accessed by \"mainN\" key" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "4c08ccb8-592d-4f80-953c-bf195e33945f", + "metadata": {}, + "outputs": [ + { + "ename": "KeyError", + "evalue": "'back0'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[8], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43mautotm\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtopics\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mback0\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m)\n", + "\u001b[0;31mKeyError\u001b[0m: 'back0'" + ] + } + ], + "source": [ + "print(autotm.topics['back0'])" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "23707b8c-9a41-49ca-9bc7-41676ccfddd1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['get', 'also', 'new', 'know', 'two', 'people', 'well', 'think', 'make', 'even', 'would', 'see', 'time', 'right', 'give', 'need', 'do', 'work', 'find', 'god', 'want', 'window', 'include', 'back', 'use', 'really', 'case', 'one', 'please', 'way', 'game', 'post', 'since', 'fact', 'etc', 'mean', 'space', 'ask', 'chip', 'cause', 'day', 'state', 'name', 'say', 'put', 'order', 'drive', 'go', 'support', 'information']\n" + ] + } + ], + "source": [ + "print(autotm.topics['main5'])" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "1abd0021-b302-42cb-89ad-6a62f9001015", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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