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cnn_dailymail_6789_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_6789_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 - liverpool - player - club 12 -1_season_league_liverpool_player
0 said - one - police - year - people 151 0_said_one_police_year
1 madrid - league - champions - real - barcelona 1070 1_madrid_league_champions_real
2 chelsea - united - manchester - van - league 55 2_chelsea_united_manchester_van
3 fight - pacquiao - ticket - mayweather - boxing 43 3_fight_pacquiao_ticket_mayweather
4 race - hamilton - rosberg - marathon - vettel 28 4_race_hamilton_rosberg_marathon
5 england - cook - pietersen - cricket - test 25 5_england_cook_pietersen_cricket
6 villa - sherwood - benteke - aston - game 19 6_villa_sherwood_benteke_aston
7 try - minute - huddersfield - bristol - league 17 7_try_minute_huddersfield_bristol
8 celtic - scottish - rangers - game - inverness 15 8_celtic_scottish_rangers_game
9 mcilroy - masters - woods - augusta - golf 14 9_mcilroy_masters_woods_augusta
10 arsenal - wenger - arsenals - reading - coquelin 14 10_arsenal_wenger_arsenals_reading
11 newcastle - sunderland - advocaat - game - rangers 13 11_newcastle_sunderland_advocaat_game
12 cup - toulon - saracens - clermont - bath 12 12_cup_toulon_saracens_clermont
13 stadium - stand - fan - fa - final 12 13_stadium_stand_fan_fa

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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