CoolFace
Modelpublic

riccardopresti99/topic_modelling_football

sourceHugging Faceupdated 3y agoView on Hugging Face
1likes6downloads
Model Card

tags:

  • —bertopic libraryname: bertopic pipelinetag: text-classification ---

topicmodellingfootball

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("riccardopresti99/topic_modelling_football")

topic_model.get_topic_info()

Topic overview

  • —Number of topics: 14
  • —Number of training documents: 350

<details> <summary>Click here for an overview of all topics.</summary>

Topic IDTopic KeywordsTopic FrequencyLabel
-1tournament - competition - leaving - final - compete16-1tournamentcompetitionleavingfinal
0video - games - football - players - experience100videogamesfootballplayers
1supporters - atmosphere - stadiums - football - create481supportersatmospherestadiumsfootball
2physiotherapists - injury - injuries - players - prevention322physiotherapistsinjuryinjuriesplayers
3united - film - football - war - story293unitedfilmfootballwar
4ronaldo - ability - scoring - aspiring - one264ronaldoabilityscoringaspiring
5scandals - illegal - officials - within - concerns265scandalsillegalofficialswithin
6healthy - footballers - energy - supports - performance256healthyfootballersenergysupports
7strikers - striker - scoring - teammates - goals257strikersstrikerscoringteammates
8investors - stock - stocks - market - club258investorsstockstocksmarket
9women - football - girls - equal - sport259womenfootballgirlsequal
10serie - milan - league - inter - italian2310seriemilanleagueinter
11champions - league - european - club - uefa2211championsleagueeuropeanclub
12cup - world - fifa - held - trophy1812cupworldfifaheld

</details>

Training hyperparameters

  • —calculate_probabilities: False
  • —language: None
  • —low_memory: False
  • —mintopicsize: 10
  • —ngramrange: (1, 1)
  • —nr_topics: None
  • —seedtopiclist: None
  • —topnwords: 10
  • —verbose: True

Framework versions

  • —Numpy: 1.23.5
  • —HDBSCAN: 0.8.29
  • —UMAP: 0.5.3
  • —Pandas: 1.5.3
  • —Scikit-Learn: 1.2.2
  • —Sentence-transformers: 2.2.2
  • —Transformers: 4.26.1
  • —Numba: 0.56.4
  • —Plotly: 5.13.1
  • —Python: 3.10.10