metadata
tags:
- bertopic
library_name: bertopic
pipeline_tag: text-classification
xsum_22457_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/xsum_22457_3000_1500_test")
topic_model.get_topic_info()
Topic overview
- Number of topics: 10
- Number of training documents: 1500
Click here for an overview of all topics.
| Topic ID | Topic Keywords | Topic Frequency | Label |
|---|---|---|---|
| -1 | said - club - player - game - football | 10 | -1_said_club_player_game |
| 0 | said - mr - people - would - year | 167 | 0_said_mr_people_would |
| 1 | kick - shot - free - goal - right | 1066 | 1_kick_shot_free_goal |
| 2 | midfielder - loan - season - club - league | 69 | 2_midfielder_loan_season_club |
| 3 | race - sport - gold - medal - olympic | 53 | 3_race_sport_gold_medal |
| 4 | celtic - club - aberdeen - cup - player | 39 | 4_celtic_club_aberdeen_cup |
| 5 | england - cricket - wicket - test - captain | 33 | 5_england_cricket_wicket_test |
| 6 | cup - wales - rugby - game - fa | 33 | 6_cup_wales_rugby_game |
| 7 | wimbledon - player - murray - im - atp | 18 | 7_wimbledon_player_murray_im |
| 8 | armstrong - banned - antidoping - rugby - sky | 12 | 8_armstrong_banned_antidoping_rugby |
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: 0.57.1
- Plotly: 5.13.1
- Python: 3.10.12