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
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