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Add BERTopic model
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metadata
tags:
  - bertopic
library_name: bertopic
pipeline_tag: text-classification

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:

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