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

# MARTINI_enrich_BERTopic_DrMikeYeadon

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("AIDA-UPM/MARTINI_enrich_BERTopic_DrMikeYeadon")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 20
* Number of training documents: 2367

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | vaccine - conspiracy - injected - everyone - gates | 24 | -1_vaccine_conspiracy_injected_everyone | 
| 0 | bob - apologies - fyi - wishing - disinformation | 1344 | 0_bob_apologies_fyi_wishing | 
| 1 | pandemics - influenza - contagious - virus - pcr | 193 | 1_pandemics_influenza_contagious_virus | 
| 2 | vaccinated - deaths - myocarditis - astrazeneca - 2022 | 122 | 2_vaccinated_deaths_myocarditis_astrazeneca | 
| 3 | vaccine - mrna - injected - omicron - toxic | 78 | 3_vaccine_mrna_injected_omicron | 
| 4 | co2 - temperatures - anthropogenic - scientists - glaciation | 75 | 4_co2_temperatures_anthropogenic_scientists | 
| 5 | vaccinations - unvaccinated - pertussis - paxlovid - infants | 61 | 5_vaccinations_unvaccinated_pertussis_paxlovid | 
| 6 | orwell - conspiracy - davos - depopulation - gatekeepers | 55 | 6_orwell_conspiracy_davos_depopulation | 
| 7 | pandemics - sovereignty - immunologically - icmra - regulations | 46 | 7_pandemics_sovereignty_immunologically_icmra | 
| 8 | hydroxychloroquine - remdesivir - ventilator - midazolam - azithromycin | 45 | 8_hydroxychloroquine_remdesivir_ventilator_midazolam | 
| 9 | vaccinations - contraceptive - hcg - stillbirths - pfizer | 44 | 9_vaccinations_contraceptive_hcg_stillbirths | 
| 10 | vaccination - biometric - passport - tyranny - mandatory | 42 | 10_vaccination_biometric_passport_tyranny | 
| 11 | fda - regulators - mra - unregulated - pharmacies | 40 | 11_fda_regulators_mra_unregulated | 
| 12 | globalists - democracy - erdogan - mayoral - arrests | 33 | 12_globalists_democracy_erdogan_mayoral | 
| 13 | fed - collateral - crisis - inflation - bonds | 31 | 13_fed_collateral_crisis_inflation | 
| 14 | yeadon - bigpharma - michael - scientist - doomsday | 28 | 14_yeadon_bigpharma_michael_scientist | 
| 15 | cashless - cbdcs - currencies - withdrawing - centralised | 28 | 15_cashless_cbdcs_currencies_withdrawing | 
| 16 | fuels - diesel - evs - emissions - engine | 27 | 16_fuels_diesel_evs_emissions | 
| 17 | parliamentarians - symposium - censored - recorded - croatia | 26 | 17_parliamentarians_symposium_censored_recorded | 
| 18 | doctors - psychiatrist - complicit - suicide - lunatic | 25 | 18_doctors_psychiatrist_complicit_suicide |
  
</details>

## Training hyperparameters

* calculate_probabilities: True
* language: None
* 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
* zeroshot_min_similarity: 0.7
* zeroshot_topic_list: None

## Framework versions

* Numpy: 1.26.4
* HDBSCAN: 0.8.40
* UMAP: 0.5.7
* Pandas: 2.2.3
* Scikit-Learn: 1.5.2
* Sentence-transformers: 3.3.1
* Transformers: 4.46.3
* Numba: 0.60.0
* Plotly: 5.24.1
* Python: 3.10.12
