xsum_123_3000_1500_validation
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_123_3000_1500_validation")
topic_model.get_topic_info()
Topic overview
- Number of topics: 27
- Number of training documents: 1500
Click here for an overview of all topics.
| Topic ID | Topic Keywords | Topic Frequency | Label |
|---|---|---|---|
| -1 | said - mr - would - also - year | 5 | -1_said_mr_would_also |
| 0 | police - said - court - mr - found | 654 | 0_police_said_court_mr |
| 1 | said - council - site - would - development | 101 | 1_said_council_site_would |
| 2 | attack - killed - taliban - syria - government | 68 | 2_attack_killed_taliban_syria |
| 3 | gold - world - race - sport - olympic | 57 | 3_gold_world_race_sport |
| 4 | price - bank - rate - share - company | 53 | 4_price_bank_rate_share |
| 5 | party - vote - labour - mr - ukip | 52 | 5_party_vote_labour_mr |
| 6 | league - season - player - premier - club | 49 | 6_league_season_player_premier |
| 7 | cricket - england - wicket - game - test | 45 | 7_cricket_england_wicket_game |
| 8 | crash - car - road - accident - said | 42 | 8_crash_car_road_accident |
| 9 | wales - game - rugby - davies - hes | 40 | 9_wales_game_rugby_davies |
| 10 | patient - health - hospital - service - ambulance | 34 | 10_patient_health_hospital_service |
| 11 | foul - corner - half - box - kick | 32 | 11_foul_corner_half_box |
| 12 | trump - clinton - mr - mrs - us | 30 | 12_trump_clinton_mr_mrs |
| 13 | president - mr - africa - south - mugabe | 30 | 13_president_mr_africa_south |
| 14 | animal - dog - bird - said - rspca | 28 | 14_animal_dog_bird_said |
| 15 | school - education - teacher - child - pupil | 26 | 15_school_education_teacher_child |
| 16 | world - round - number - murray - court | 25 | 16_world_round_number_murray |
| 17 | northern - ireland - party - dup - sinn | 23 | 17_northern_ireland_party_dup |
| 18 | album - song - like - music - band | 17 | 18_album_song_like_music |
| 19 | fire - building - police - blaze - service | 16 | 19_fire_building_police_blaze |
| 20 | fossil - brontosaurus - dinosaur - found - animal | 16 | 20_fossil_brontosaurus_dinosaur_found |
| 21 | film - star - artist - novel - photograph | 16 | 21_film_star_artist_novel |
| 22 | wage - income - living - tax - uk | 11 | 22_wage_income_living_tax |
| 23 | gang - guerrero - prison - state - police | 11 | 23_gang_guerrero_prison_state |
| 24 | albion - brighton - hove - burton - wigan | 11 | 24_albion_brighton_hove_burton |
| 25 | 3d - space - kelly - cmdr - flight | 8 | 25_3d_space_kelly_cmdr |
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
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