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KingKazma/
cnn_dailymail_108_3000_1500_test

Name: cnn_dailymail_108_3000_1500_test
Availability: InStock

bertopic

text-classification

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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:

python

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