|
|
| --- |
| tags: |
| - bertopic |
| library_name: bertopic |
| pipeline_tag: text-classification |
| --- |
| |
| # MARTINI_enrich_BERTopic_ConPy |
| |
| 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_ConPy") |
| |
| topic_model.get_topic_info() |
| ``` |
| |
| ## Topic overview |
| |
| * Number of topics: 9 |
| * Number of training documents: 921 |
| |
| <details> |
| <summary>Click here for an overview of all topics.</summary> |
| |
| | Topic ID | Topic Keywords | Topic Frequency | Label | |
| |----------|----------------|-----------------|-------| |
| | -1 | tucker - cuomo - supreme - immigration - subtitles | 38 | -1_tucker_cuomo_supreme_immigration | |
| | 0 | fauci - unvaxed - tyranny - jab - mandates | 374 | 0_fauci_unvaxed_tyranny_jab | |
| | 1 | tucker - fauci - tonight - taliban - democrats | 155 | 1_tucker_fauci_tonight_taliban | |
| | 2 | tucker - foxnews - tonight - presidential - 2020 | 86 | 2_tucker_foxnews_tonight_presidential | |
| | 3 | tucker - tonight - texas - migrants - governor | 71 | 3_tucker_tonight_texas_migrants | |
| | 4 | jfk - undercover - ufo - documentary - assassination | 62 | 4_jfk_undercover_ufo_documentary | |
| | 5 | tucker - carlson - zelensky - tonight - invading | 55 | 5_tucker_carlson_zelensky_tonight | |
| | 6 | fauci - unvaxed - david - podcast - tyranny | 41 | 6_fauci_unvaxed_david_podcast | |
| | 7 | crimea - sanctions - ussr - ukrainian - sovereignty | 39 | 7_crimea_sanctions_ussr_ukrainian | |
| |
| </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 |
| |
