bertopic text-classification region:us
---
library_name: bertopic
pipeline_tag: text-classification
tags:
- bertopic
---

# xsum_108_50000_25000_test

This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model. 
BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets. 

## Usage 

To use this model, please install BERTopic:

```
pip install -U bertopic
```

You can use the model as follows:

```python
from bertopic import BERTopic
topic_model = BERTopic.load("KingKazma/xsum_108_50000_25000_test")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 84
* Number of training documents: 11334

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | said - mr - people - would - year | 5 | -1_said_mr_people_would | 
| 0 | win - goal - game - league - foul | 4854 | 0_win_goal_game_league | 
| 1 | police - court - said - officer - mr | 1637 | 1_police_court_said_officer | 
| 2 | labour - party - eu - election - vote | 872 | 2_labour_party_eu_election | 
| 3 | health - care - nhs - patient - cancer | 341 | 3_health_care_nhs_patient | 
| 4 | olympic - sport - race - gold - medal | 325 | 4_olympic_sport_race_gold | 
| 5 | cricket - england - wicket - test - captain | 278 | 5_cricket_england_wicket_test | 
| 6 | animal - dog - bird - whale - specie | 206 | 6_animal_dog_bird_whale | 
| 7 | bridge - rail - council - said - transport | 199 | 7_bridge_rail_council_said | 
| 8 | school - education - student - teacher - university | 193 | 8_school_education_student_teacher | 
| 9 | bank - rate - growth - economy - market | 181 | 9_bank_rate_growth_economy | 
| 10 | syria - syrian - iraq - iran - force | 145 | 10_syria_syrian_iraq_iran | 
| 11 | energy - industry - wind - electricity - company | 119 | 11_energy_industry_wind_electricity | 
| 12 | film - actress - star - actor - character | 80 | 12_film_actress_star_actor | 
| 13 | president - boko - african - haram - mr | 79 | 13_president_boko_african_haram | 
| 14 | fire - blaze - service - smoke - said | 79 | 14_fire_blaze_service_smoke | 
| 15 | trump - mr - republican - trumps - president | 75 | 15_trump_mr_republican_trumps | 
| 16 | music - album - song - band - singer | 70 | 16_music_album_song_band | 
| 17 | race - hamilton - f1 - mercedes - lap | 68 | 17_race_hamilton_f1_mercedes | 
| 18 | space - earth - planet - solar - orbit | 61 | 18_space_earth_planet_solar | 
| 19 | lifeboat - rnli - beach - coastguard - rescue | 55 | 19_lifeboat_rnli_beach_coastguard | 
| 20 | flood - flooding - water - weather - rain | 55 | 20_flood_flooding_water_weather | 
| 21 | fight - boxing - champion - joshua - ali | 54 | 21_fight_boxing_champion_joshua | 
| 22 | plane - aircraft - flight - passenger - pilot | 54 | 22_plane_aircraft_flight_passenger | 
| 23 | earthquake - quake - flood - people - water | 53 | 23_earthquake_quake_flood_people | 
| 24 | russian - russia - ukraine - putin - ukrainian | 49 | 24_russian_russia_ukraine_putin | 
| 25 | murray - match - wimbledon - tennis - konta | 47 | 25_murray_match_wimbledon_tennis | 
| 26 | bitcoin - security - talktalk - data - tor | 44 | 26_bitcoin_security_talktalk_data | 
| 27 | round - birdie - bogey - par - shot | 41 | 27_round_birdie_bogey_par | 
| 28 | ireland - dup - sinn - northern - party | 39 | 28_ireland_dup_sinn_northern | 
| 29 | maduro - venezuela - president - venezuelan - opposition | 36 | 29_maduro_venezuela_president_venezuelan | 
| 30 | yn - ar - yr - ei - wedi | 36 | 30_yn_ar_yr_ei | 
| 31 | painting - art - gallery - portrait - museum | 34 | 31_painting_art_gallery_portrait | 
| 32 | unsupported - updated - bst - playback - media | 33 | 32_unsupported_updated_bst_playback | 
| 33 | migrant - eu - asylum - turkey - germany | 31 | 33_migrant_eu_asylum_turkey | 
| 34 | stone - cave - discovery - site - tree | 30 | 34_stone_cave_discovery_site | 
| 35 | parade - poppy - flag - jesus - statue | 30 | 35_parade_poppy_flag_jesus | 
| 36 | drug - cannabis - drugs - heroin - cocaine | 27 | 36_drug_cannabis_drugs_heroin | 
| 37 | church - pope - bishop - vatican - cardinal | 27 | 37_church_pope_bishop_vatican | 
| 38 | greek - greece - bailout - eurozone - bank | 27 | 38_greek_greece_bailout_eurozone | 
| 39 | nama - ireland - northern - cerberus - irish | 26 | 39_nama_ireland_northern_cerberus | 
| 40 | prison - prisoner - prisons - justice - turing | 25 | 40_prison_prisoner_prisons_justice | 
| 41 | radio - show - bbc - series - programme | 24 | 41_radio_show_bbc_series | 
| 42 | fifa - blatter - platini - fifas - football | 23 | 42_fifa_blatter_platini_fifas | 
| 43 | tesco - sale - store - supermarket - customer | 23 | 43_tesco_sale_store_supermarket | 
| 44 | china - taiwan - chinese - hong - taiwans | 22 | 44_china_taiwan_chinese_hong | 
| 45 | afghan - taliban - afghanistan - mansour - mullah | 22 | 45_afghan_taliban_afghanistan_mansour | 
| 46 | council - local - funding - government - authority | 22 | 46_council_local_funding_government | 
| 47 | nsa - encryption - cia - snowden - us | 21 | 47_nsa_encryption_cia_snowden | 
| 48 | ice - glacier - temperature - ocean - climate | 21 | 48_ice_glacier_temperature_ocean | 
| 49 | osullivan - world - snooker - beat - champion | 21 | 49_osullivan_world_snooker_beat | 
| 50 | book - prize - novel - author - award | 20 | 50_book_prize_novel_author | 
| 51 | auschwitz - jews - holocaust - camp - winton | 20 | 51_auschwitz_jews_holocaust_camp | 
| 52 | samsung - apple - phone - company - battery | 19 | 52_samsung_apple_phone_company | 
| 53 | picture - image - pictures - please - submit | 19 | 53_picture_image_pictures_please | 
| 54 | korea - north - korean - missile - koreas | 19 | 54_korea_north_korean_missile | 
| 55 | pension - worker - pay - work - hour | 19 | 55_pension_worker_pay_work | 
| 56 | pen - fillon - le - macron - mr | 18 | 56_pen_fillon_le_macron | 
| 57 | paris - eaw - french - attack - suspect | 18 | 57_paris_eaw_french_attack | 
| 58 | content - app - tv - digital - apple | 18 | 58_content_app_tv_digital | 
| 59 | israel - israeli - palestinians - palestinian - gaza | 17 | 59_israel_israeli_palestinians_palestinian | 
| 60 | housing - affordable - rent - homelessness - government | 17 | 60_housing_affordable_rent_homelessness | 
| 61 | prince - queen - birthday - duke - royal | 17 | 61_prince_queen_birthday_duke | 
| 62 | australia - australian - asylum - visa - abbott | 15 | 62_australia_australian_asylum_visa | 
| 63 | tax - spending - cut - osborne - fiscal | 15 | 63_tax_spending_cut_osborne | 
| 64 | updated - 2017 - bst - last - gmt | 14 | 64_updated_2017_bst_last | 
| 65 | refugee - uk - child - vulnerable - refugees | 12 | 65_refugee_uk_child_vulnerable | 
| 66 | ebola - sierra - leone - outbreak - liberia | 12 | 66_ebola_sierra_leone_outbreak | 
| 67 | shah - ahmed - mosque - muslims - prophet | 11 | 67_shah_ahmed_mosque_muslims | 
| 68 | broadband - 4g - ee - customer - internet | 11 | 68_broadband_4g_ee_customer | 
| 69 | pistorius - steenkamp - toilet - door - reeva | 10 | 69_pistorius_steenkamp_toilet_door | 
| 70 | eu - uk - population - migrant - trade | 9 | 70_eu_uk_population_migrant | 
| 71 | australia - marriage - turnbull - katter - samesex | 9 | 71_australia_marriage_turnbull_katter | 
| 72 | sugar - gin - sabmiller - inbev - ab | 8 | 72_sugar_gin_sabmiller_inbev | 
| 73 | suu - kyi - rohingya - rakhine - myanmar | 8 | 73_suu_kyi_rohingya_rakhine | 
| 74 | nadeau - field - aircraft - cordon - accidents | 8 | 74_nadeau_field_aircraft_cordon | 
| 75 | abortion - ireland - law - unborn - case | 8 | 75_abortion_ireland_law_unborn | 
| 76 | homosexuality - tor - homosexual - law - gay | 7 | 76_homosexuality_tor_homosexual_law | 
| 77 | castro - cuba - cuban - fidel - havana | 7 | 77_castro_cuba_cuban_fidel | 
| 78 | china - samsung - firm - business - cheil | 7 | 78_china_samsung_firm_business | 
| 79 | event - festival - technology - campsite - interactive | 6 | 79_event_festival_technology_campsite | 
| 80 | vw - volkswagen - production - emission - carmaker | 6 | 80_vw_volkswagen_production_emission | 
| 81 | mohammed - gjolla - sheriff - nca - terrorism | 6 | 81_mohammed_gjolla_sheriff_nca | 
| 82 | tb - tuberculosis - disease - badger - zoonotic | 5 | 82_tb_tuberculosis_disease_badger |
  
</details>

## Training hyperparameters

* calculate_probabilities: True
* language: english
* low_memory: False
* min_topic_size: 10
* n_gram_range: (1, 1)
* nr_topics: None
* seed_topic_list: None
* top_n_words: 10
* verbose: False

## Framework versions

* Numpy: 1.22.4
* HDBSCAN: 0.8.33
* UMAP: 0.5.3
* Pandas: 1.5.3
* Scikit-Learn: 1.2.2
* Sentence-transformers: 2.2.2
* Transformers: 4.31.0
* Numba: 0.57.1
* Plotly: 5.13.1
* Python: 3.10.12
