|
|
|
--- |
|
tags: |
|
- bertopic |
|
library_name: bertopic |
|
pipeline_tag: text-classification |
|
--- |
|
|
|
# BERTopic-2024-05-02-165545 |
|
|
|
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("Jerado/BERTopic-2024-05-02-165545") |
|
|
|
topic_model.get_topic_info() |
|
``` |
|
|
|
## Topic overview |
|
|
|
* Number of topics: 17 |
|
* Number of training documents: 1000 |
|
|
|
<details> |
|
<summary>Click here for an overview of all topics.</summary> |
|
|
|
| Topic ID | Topic Keywords | Topic Frequency | Label | |
|
|----------|----------------|-----------------|-------| |
|
| -1 | theism - much - way - think - just | 15 | -1_theism_much_way_think | |
|
| 0 | nhl - playoffs - rangers - hockey - league | 304 | 0_nhl_playoffs_rangers_hockey | |
|
| 1 | performance - ram - drivers - monitor - speed | 92 | 1_performance_ram_drivers_monitor | |
|
| 2 | x11r5 - hyperhelp - windows - pc - application | 82 | 2_x11r5_hyperhelp_windows_pc | |
|
| 3 | dos - windows - harddisk - disk - software | 82 | 3_dos_windows_harddisk_disk | |
|
| 4 | amp - amps - amplifier - ampere - current | 75 | 4_amp_amps_amplifier_ampere | |
|
| 5 | scripture - christians - sin - bible - commandment | 44 | 5_scripture_christians_sin_bible | |
|
| 6 | patients - biological - medicine - studies - doctors | 41 | 6_patients_biological_medicine_studies | |
|
| 7 | nasa - solar - space - shuttle - orbiting | 39 | 7_nasa_solar_space_shuttle | |
|
| 8 | armenians - armenian - armenia - turks - genocide | 38 | 8_armenians_armenian_armenia_turks | |
|
| 9 | guns - gun - amendment - constitution - laws | 36 | 9_guns_gun_amendment_constitution | |
|
| 10 | - - - - | 33 | 10____ | |
|
| 11 | motorcycle - bikes - cobralinks - bike - riding | 32 | 11_motorcycle_bikes_cobralinks_bike | |
|
| 12 | encryption - security - encrypted - privacy - secure | 24 | 12_encryption_security_encrypted_privacy | |
|
| 13 | contacted - address - mail - contact - email | 23 | 13_contacted_address_mail_contact | |
|
| 14 | paganism - faith - christianity - christians - atheists | 21 | 14_paganism_faith_christianity_christians | |
|
| 15 | action - fbi - batf - war - president | 19 | 15_action_fbi_batf_war | |
|
|
|
</details> |
|
|
|
## Training hyperparameters |
|
|
|
* calculate_probabilities: False |
|
* language: english |
|
* low_memory: False |
|
* min_topic_size: 10 |
|
* n_gram_range: (1, 1) |
|
* nr_topics: None |
|
* seed_topic_list: [['drug', 'cancer', 'drugs', 'doctor'], ['windows', 'drive', 'dos', 'file'], ['space', 'launch', 'orbit', 'lunar']] |
|
* top_n_words: 10 |
|
* verbose: False |
|
* zeroshot_min_similarity: 0.7 |
|
* zeroshot_topic_list: None |
|
|
|
## Framework versions |
|
|
|
* Numpy: 1.23.5 |
|
* HDBSCAN: 0.8.33 |
|
* UMAP: 0.5.6 |
|
* Pandas: 2.0.3 |
|
* Scikit-Learn: 1.2.2 |
|
* Sentence-transformers: 2.7.0 |
|
* Transformers: 4.40.1 |
|
* Numba: 0.58.1 |
|
* Plotly: 5.15.0 |
|
* Python: 3.10.12 |
|
|
