cnn_dailymail_108_3000_1500_test
This is a 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:
from bertopic import BERTopic
topic_model = BERTopic.load("KingKazma/cnn_dailymail_108_3000_1500_test")
topic_model.get_topic_info()
Topic overview
- Number of topics: 29
- Number of training documents: 1500
Click here for an overview of all topics.
| Topic ID | Topic Keywords | Topic Frequency | Label |
|---|---|---|---|
| -1 | said - one - year - time - people | 11 | -1_said_one_year_time |
| 0 | police - said - told - school - court | 384 | 0_police_said_told_school |
| 1 | game - liverpool - league - goal - season | 249 | 1_game_liverpool_league_goal |
| 2 | said - attack - group - police - people | 91 | 2_said_attack_group_police |
| 3 | people - said - planet - mountain - mile | 85 | 3_people_said_planet_mountain |
| 4 | baby - family - mother - said - cancer | 77 | 4_baby_family_mother_said |
| 5 | labour - mr - miliband - tax - leader | 54 | 5_labour_mr_miliband_tax |
| 6 | shark - crocodile - fish - animal - water | 49 | 6_shark_crocodile_fish_animal |
| 7 | chelsea - arsenal - mourinho - hazard - league | 37 | 7_chelsea_arsenal_mourinho_hazard |
| 8 | united - manchester - city - van - league | 36 | 8_united_manchester_city_van |
| 9 | masters - round - woods - group - tournament | 31 | 9_masters_round_woods_group |
| 10 | model - fashion - dress - woman - look | 30 | 10_model_fashion_dress_woman |
| 11 | food - sugar - restaurant - water - vitamin | 29 | 11_food_sugar_restaurant_water |
| 12 | race - hamilton - rosberg - grand - prix | 29 | 12_race_hamilton_rosberg_grand |
| 13 | madrid - ronaldo - real - goal - barcelona | 29 | 13_madrid_ronaldo_real_goal |
| 14 | england - cricket - test - cook - benaud | 28 | 14_england_cricket_test_cook |
| 15 | clinton - president - obama - hillary - said | 27 | 15_clinton_president_obama_hillary |
| 16 | property - house - home - market - apartment | 25 | 16_property_house_home_market |
| 17 | fight - mayweather - pacquiao - manny - bout | 25 | 17_fight_mayweather_pacquiao_manny |
| 18 | apple - watch - price - per - cent | 24 | 18_apple_watch_price_per |
| 19 | celtic - rangers - game - scottish - deila | 24 | 19_celtic_rangers_game_scottish |
| 20 | dog - animal - owner - council - dogs | 21 | 20_dog_animal_owner_council |
| 21 | prince - royal - harry - queen - baby | 21 | 21_prince_royal_harry_queen |
| 22 | film - actor - downey - interview - show | 17 | 22_film_actor_downey_interview |
| 23 | hotel - flight - mile - island - room | 16 | 23_hotel_flight_mile_island |
| 24 | bayern - guardiola - porto - dortmund - munich | 14 | 24_bayern_guardiola_porto_dortmund |
| 25 | wedding - gabriel - noah - roxy - sandra | 13 | 25_wedding_gabriel_noah_roxy |
| 26 | saracens - bosch - penalty - kick - rugby | 12 | 26_saracens_bosch_penalty_kick |
| 27 | deal - summer - club - interest - contract | 12 | 27_deal_summer_club_interest |
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: 0.56.4
- Plotly: 5.13.1
- Python: 3.10.6
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