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KingKazma/
cnn_dailymail_55555_3000_1500_test

Name: cnn_dailymail_55555_3000_1500_test
Availability: InStock

bertopic

text-classification

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cnn_dailymail_55555_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_55555_3000_1500_test")

topic_model.get_topic_info()

Topic overview

Number of topics: 15
Number of training documents: 1500

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
-1	season - league - player - club - game	13	-1_season_league_player_club
0	said - one - people - year - also	121	0_said_one_people_year
1	madrid - real - barcelona - league - atletico	1080	1_madrid_real_barcelona_league
2	sterling - liverpool - league - club - season	41	2_sterling_liverpool_league_club
3	try - game - minute - wolves - back	35	3_try_game_minute_wolves
4	chelsea - league - hazard - premier - mourinho	27	4_chelsea_league_hazard_premier
5	lady - race - djokovic - victory - oxford	24	5_lady_race_djokovic_victory
6	england - cricket - test - wicket - pietersen	24	6_england_cricket_test_wicket
7	villa - sherwood - liverpool - cup - fa	23	7_villa_sherwood_liverpool_cup
8	united - manchester - van - gaal - carrick	23	8_united_manchester_van_gaal
9	fight - mayweather - pacquiao - ticket - manny	23	9_fight_mayweather_pacquiao_ticket
10	bayern - guardiola - munich - porto - ribery	21	10_bayern_guardiola_munich_porto
11	masters - woods - augusta - mcilroy - shot	16	11_masters_woods_augusta_mcilroy
12	rangers - scottish - game - celtic - hearts	15	12_rangers_scottish_game_celtic
13	race - hamilton - rosberg - car - ferrari	14	13_race_hamilton_rosberg_car

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