predict_rugby

predict_rugby

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("rociortizb/predict_rugby")

topic_model.get_topic_info()

Topic overview

• Number of topics: 40
• Number of training documents: 27774

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

Training hyperparameters

• calculate_probabilities: False
• language: None
• low_memory: False
• min_topic_size: 10
• n_gram_range: (1, 1)
• nr_topics: None
• seed_topic_list: [['United Rugby Championship', 'Ireland', 'Wales', 'Scotland', 'South Africa', 'Italian', 'Pro14'], ['Pro14', 'Edinburgh', 'Glasgow', 'Scarlets', 'Ospreys', 'Zebre', 'Benetton', 'Connacht', 'Leinster', 'Ulster', 'Munster'], ['European Cup', 'European', 'Heineken', 'competition', 'Toulon', 'Saracens', 'Leinster'], ['Premiership', 'England', 'Exeter', 'Saracens', 'Wasps', 'Leicester', 'Harlequins', 'Sale', 'Bristol', 'Northampton'], ['Sevens', 'Fiji', 'New Zealand', 'South Africa', 'England', 'Australia', 'series', 'HSBC', 'Olympics'], ['Super Rugby', 'New Zealand', 'Australia', 'South Africa', 'Argentina', 'Japan', 'Blues', 'Brumbies', 'Crusaders', 'Sharks', 'Stormers'], ['Six Nations', 'England', 'Wales', 'Ireland', 'Scotland', 'France', 'Italy', 'Championship', 'Grand Slam'], ['Currie Cup', 'South Africa', 'Bulls', 'Lions', 'Sharks', 'Cheetahs', 'Western Province', 'domestic', 'provincial'], ['World Cup', 'international', 'New Zealand', 'Australia', 'South Africa', 'England', 'Wales', 'France'], ['Rugby Championship', 'New Zealand', 'Australia', 'South Africa', 'Argentina', 'All Blacks', 'Wallabies', 'Springboks', 'Pumas'], ['British Irish Lions', 'South Africa', 'New Zealand', 'Australia']]
• top_n_words: 30
• verbose: True

Framework versions

• Numpy: 1.21.0
• HDBSCAN: 0.8.29
• UMAP: 0.5.3
• Pandas: 2.0.2
• Scikit-Learn: 1.2.2
• Sentence-transformers: 2.2.2
• Transformers: 4.29.2
• Numba: 0.57.0
• Plotly: 5.14.1
• Python: 3.9.6