| |
|
| | --- |
| | tags: |
| | - bertopic |
| | library_name: bertopic |
| | pipeline_tag: text-classification |
| | --- |
| | |
| | # MARTINI_enrich_BERTopic_afldscc |
| | |
| | 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_afldscc") |
| | |
| | topic_model.get_topic_info() |
| | ``` |
| | |
| | ## Topic overview |
| | |
| | * Number of topics: 14 |
| | * Number of training documents: 1099 |
| | |
| | <details> |
| | <summary>Click here for an overview of all topics.</summary> |
| | |
| | | Topic ID | Topic Keywords | Topic Frequency | Label | |
| | |----------|----------------|-----------------|-------| |
| | | -1 | vaccine - cdc - ivermectin - zelenko - 2022 | 24 | -1_vaccine_cdc_ivermectin_zelenko | |
| | | 0 | physicians - rilegislature - california - unconstitutional - hb2280 | 549 | 0_physicians_rilegislature_california_unconstitutional | |
| | | 1 | vaccine - reinstated - mandates - cuomo - refusing | 76 | 1_vaccine_reinstated_mandates_cuomo | |
| | | 2 | freedrgold - simone - supporters - pma - sentencing | 57 | 2_freedrgold_simone_supporters_pma | |
| | | 3 | reawaken - stateline - clark - event - speedway | 55 | 3_reawaken_stateline_clark_event | |
| | | 4 | freedom - days - injustices - flyer - defendants | 50 | 4_freedom_days_injustices_flyer | |
| | | 5 | scotus - redress - tyranny - senators - brunson | 47 | 5_scotus_redress_tyranny_senators | |
| | | 6 | vaccine - myocarditis - paxlovid - deaths - 2021 | 42 | 6_vaccine_myocarditis_paxlovid_deaths | |
| | | 7 | citizencorps - aflds - meeting - dana - joined | 38 | 7_citizencorps_aflds_meeting_dana | |
| | | 8 | pfizer - fauci - publicis - disinformation - fbi | 38 | 8_pfizer_fauci_publicis_disinformation | |
| | | 9 | homeschool - educate - resources - christa - explore | 37 | 9_homeschool_educate_resources_christa | |
| | | 10 | novavax - fda - injections - infants - 2022 | 31 | 10_novavax_fda_injections_infants | |
| | | 11 | lockdowns - masks - effects - harmful - kaiser | 29 | 11_lockdowns_masks_effects_harmful | |
| | | 12 | pandemics - stopthewho - sovereignty - amendments - geneva | 26 | 12_pandemics_stopthewho_sovereignty_amendments | |
| | |
| | </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 |
| | |
