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

# cnn_dailymail_123_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_123_3000_1500_test")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 12
* Number of training documents: 1500

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | league - season - klopp - game - club | 13 | -1_league_season_klopp_game | 
| 0 | said - one - year - also - people | 73 | 0_said_one_year_also | 
| 1 | liverpool - player - club - sterling - league | 1088 | 1_liverpool_player_club_sterling | 
| 2 | league - goal - madrid - barcelona - champions | 91 | 2_league_goal_madrid_barcelona | 
| 3 | manchester - united - city - van - gaal | 51 | 3_manchester_united_city_van | 
| 4 | world - first - woods - hamilton - win | 38 | 4_world_first_woods_hamilton | 
| 5 | england - cricket - test - captain - pietersen | 35 | 5_england_cricket_test_captain | 
| 6 | celtic - game - inverness - rangers - player | 31 | 6_celtic_game_inverness_rangers | 
| 7 | mayweather - fight - pacquiao - vegas - las | 28 | 7_mayweather_fight_pacquiao_vegas | 
| 8 | mccoy - national - lady - ride - race | 23 | 8_mccoy_national_lady_ride | 
| 9 | clermont - saracens - cup - england - northampton | 16 | 9_clermont_saracens_cup_england | 
| 10 | chelsea - mourinho - stoke - league - game | 13 | 10_chelsea_mourinho_stoke_league |
  
</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