xsum_108_5000000_2500000_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_108_5000000_2500000_test")
topic_model.get_topic_info()
Topic overview
- Number of topics: 14
- Number of training documents: 11334
Click here for an overview of all topics.
| Topic ID | Topic Keywords | Topic Frequency | Label |
|---|---|---|---|
| -1 | said - win - first - one - time | 13 | -1_said_win_first_one |
| 0 | said - mr - would - people - also | 1003 | 0_said_mr_would_people |
| 1 | win - game - league - goal - right | 7868 | 1_win_game_league_goal |
| 2 | race - olympic - sport - gold - team | 1707 | 2_race_olympic_sport_gold |
| 3 | england - cricket - wicket - test - captain | 225 | 3_england_cricket_wicket_test |
| 4 | race - hamilton - mercedes - f1 - lap | 192 | 4_race_hamilton_mercedes_f1 |
| 5 | match - murray - konta - seed - set | 62 | 5_match_murray_konta_seed |
| 6 | round - birdie - shot - par - bogey | 59 | 6_round_birdie_shot_par |
| 7 | fight - boxing - champion - ali - title | 49 | 7_fight_boxing_champion_ali |
| 8 | yn - ar - ei - yr - wedi | 48 | 8_yn_ar_ei_yr |
| 9 | unsupported - updated - playback - media - device | 33 | 9_unsupported_updated_playback_media |
| 10 | world - champion - osullivan - event - snooker | 29 | 10_world_champion_osullivan_event |
| 11 | fifa - blatter - football - platini - fifas | 25 | 11_fifa_blatter_football_platini |
| 12 | ebola - sierra - leone - outbreak - people | 21 | 12_ebola_sierra_leone_outbreak |
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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