---
tags:
- bertopic
library_name: bertopic
pipeline_tag: text-classification
---

# cnn_dailymail_6789_3000_1500_test

This is a [BERTopic](https://github.com/MaartenGr/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:

```python
from bertopic import BERTopic
topic_model = BERTopic.load("KingKazma/cnn_dailymail_6789_3000_1500_test")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 15
* Number of training documents: 1500

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | season - league - liverpool - player - club | 12 | -1_season_league_liverpool_player | 
| 0 | said - one - police - year - people | 151 | 0_said_one_police_year | 
| 1 | madrid - league - champions - real - barcelona | 1070 | 1_madrid_league_champions_real | 
| 2 | chelsea - united - manchester - van - league | 55 | 2_chelsea_united_manchester_van | 
| 3 | fight - pacquiao - ticket - mayweather - boxing | 43 | 3_fight_pacquiao_ticket_mayweather | 
| 4 | race - hamilton - rosberg - marathon - vettel | 28 | 4_race_hamilton_rosberg_marathon | 
| 5 | england - cook - pietersen - cricket - test | 25 | 5_england_cook_pietersen_cricket | 
| 6 | villa - sherwood - benteke - aston - game | 19 | 6_villa_sherwood_benteke_aston | 
| 7 | try - minute - huddersfield - bristol - league | 17 | 7_try_minute_huddersfield_bristol | 
| 8 | celtic - scottish - rangers - game - inverness | 15 | 8_celtic_scottish_rangers_game | 
| 9 | mcilroy - masters - woods - augusta - golf | 14 | 9_mcilroy_masters_woods_augusta | 
| 10 | arsenal - wenger - arsenals - reading - coquelin | 14 | 10_arsenal_wenger_arsenals_reading | 
| 11 | newcastle - sunderland - advocaat - game - rangers | 13 | 11_newcastle_sunderland_advocaat_game | 
| 12 | cup - toulon - saracens - clermont - bath | 12 | 12_cup_toulon_saracens_clermont | 
| 13 | stadium - stand - fan - fa - final | 12 | 13_stadium_stand_fan_fa |
  
</details>

## 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