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--- |
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tags: |
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- bertopic |
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library_name: bertopic |
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pipeline_tag: text-classification |
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--- |
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# bertopic_WGnews_Oct31 |
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This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model. |
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BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets. |
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## Usage |
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To use this model, please install BERTopic: |
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``` |
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pip install -U bertopic |
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``` |
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You can use the model as follows: |
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```python |
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from bertopic import BERTopic |
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topic_model = BERTopic.load("tyrealqian/bertopic_WGnews_Oct31") |
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topic_model.get_topic_info() |
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``` |
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## Topic overview |
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* Number of topics: 28 |
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* Number of training documents: 6196 |
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<details> |
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<summary>Click here for an overview of all topics.</summary> |
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| Topic ID | Topic Keywords | Topic Frequency | Label | |
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|----------|----------------|-----------------|-------| |
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| -1 | beijing - winter - olympics - winter olympics - olympic | 18 | -1_beijing_winter_olympics_winter olympics | |
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| 0 | gold - medal - olympics - beijing - womens | 2054 | 0_gold_medal_olympics_beijing | |
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| 1 | covid - olympics - beijing - cases - winter | 633 | 1_covid_olympics_beijing_cases | |
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| 2 | gold - gu - womens - chinas - mens | 524 | 2_gold_gu_womens_chinas | |
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| 3 | president - xi - xi jinping - jinping - president xi | 388 | 3_president_xi_xi jinping_jinping | |
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| 4 | boycott - diplomatic - diplomatic boycott - boycott beijing - rights | 372 | 4_boycott_diplomatic_diplomatic boycott_boycott beijing | |
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| 5 | dwen - mascot - bing - bing dwen - dwen dwen | 328 | 5_dwen_mascot_bing_bing dwen | |
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| 6 | ceremony - opening - opening ceremony - beijing - ceremony beijing | 305 | 6_ceremony_opening_opening ceremony_beijing | |
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| 7 | kamila - valieva - kamila valieva - russian - figure | 249 | 7_kamila_valieva_kamila valieva_russian | |
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| 8 | torch - flame - relay - torch relay - olympic | 208 | 8_torch_flame_relay_torch relay | |
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| 9 | venue - ice - venues - zhangjiakou - beijing | 194 | 9_venue_ice_venues_zhangjiakou | |
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| 10 | sports - winter sports - winter - globalink - snow | 159 | 10_sports_winter sports_winter_globalink | |
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| 11 | food - robot - robots - served - serving | 122 | 11_food_robot_robots_served | |
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| 12 | green - carbon - games - beijing - winter | 120 | 12_green_carbon_games_beijing | |
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| 13 | coverage - heres - day - olympics - gold | 90 | 13_coverage_heres_day_olympics | |
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| 14 | bach - thomas bach - thomas - president thomas - ioc | 59 | 14_bach_thomas bach_thomas_president thomas | |
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| 15 | snow - snowfall - heavy - weather - heavy snowfall | 48 | 15_snow_snowfall_heavy_weather | |
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| 16 | bank - commemorative - digital - yuan - set | 43 | 16_bank_commemorative_digital_yuan | |
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| 17 | paralympic - paralympic games - games - paralympic winter - winter paralympic | 37 | 17_paralympic_paralympic games_games_paralympic winter | |
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| 18 | phones - personal - burner - app - smartphonelike | 34 | 18_phones_personal_burner_app | |
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| 19 | nbc - nbcuniversal - ads - ratings - nbcs | 31 | 19_nbc_nbcuniversal_ads_ratings | |
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| 20 | watch beijing - watch - athletes watch - know - names | 27 | 20_watch beijing_watch_athletes watch_know | |
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| 21 | ukraine - invasion - russian - invasion ukraine - ukraine beijing | 27 | 21_ukraine_invasion_russian_invasion ukraine | |
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| 22 | city - summer winter - summer - host summer - city host | 27 | 22_city_summer winter_summer_host summer | |
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| 23 | leduc - nonbinary - timothy leduc - timothy - openly | 26 | 23_leduc_nonbinary_timothy leduc_timothy | |
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| 24 | ralph lauren - lauren - ralph - uniforms - team | 26 | 24_ralph lauren_lauren_ralph_uniforms | |
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| 25 | peng - shuai - peng shuai - tennis - chinese tennis | 25 | 25_peng_shuai_peng shuai_tennis | |
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| 26 | women - female athletes - record - athletes - female | 22 | 26_women_female athletes_record_athletes | |
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</details> |
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## Training hyperparameters |
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* calculate_probabilities: True |
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* language: None |
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* low_memory: False |
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* min_topic_size: 10 |
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* n_gram_range: (1, 1) |
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* nr_topics: None |
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* seed_topic_list: None |
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* top_n_words: 10 |
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* verbose: True |
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* zeroshot_min_similarity: 0.7 |
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* zeroshot_topic_list: None |
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## Framework versions |
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* Numpy: 1.26.4 |
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* HDBSCAN: 0.8.39 |
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* UMAP: 0.5.7 |
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* Pandas: 2.2.2 |
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* Scikit-Learn: 1.5.2 |
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* Sentence-transformers: 3.2.1 |
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* Transformers: 4.44.2 |
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* Numba: 0.60.0 |
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* Plotly: 5.24.1 |
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* Python: 3.10.12 |
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