| |
|
| | --- |
| | tags: |
| | - bertopic |
| | library_name: bertopic |
| | pipeline_tag: text-classification |
| | --- |
| | |
| | # MARTINI_enrich_BERTopic_RevealedEye |
| | |
| | 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_RevealedEye") |
| | |
| | topic_model.get_topic_info() |
| | ``` |
| | |
| | ## Topic overview |
| | |
| | * Number of topics: 25 |
| | * Number of training documents: 2198 |
| | |
| | <details> |
| | <summary>Click here for an overview of all topics.</summary> |
| | |
| | | Topic ID | Topic Keywords | Topic Frequency | Label | |
| | |----------|----------------|-----------------|-------| |
| | | -1 | conspiracy - population - china - rothschild - ultra | 20 | -1_conspiracy_population_china_rothschild | |
| | | 0 | fauci - vaccines - unvaccinated - pfizer - remdesivir | 916 | 0_fauci_vaccines_unvaccinated_pfizer | |
| | | 1 | illuminati - baphomet - satanic - hitchens - rituals | 116 | 1_illuminati_baphomet_satanic_hitchens | |
| | | 2 | electric - coils - nikola - 432hz - resonance | 102 | 2_electric_coils_nikola_432hz | |
| | | 3 | turmeric - syrup - colds - ingredients - antioxidants | 100 | 3_turmeric_syrup_colds_ingredients | |
| | | 4 | nutrients - parabens - organic - beef - fda | 94 | 4_nutrients_parabens_organic_beef | |
| | | 5 | chemtrails - clouds - ionospheric - spraying - artificially | 80 | 5_chemtrails_clouds_ionospheric_spraying | |
| | | 6 | speak - never - bombarded - lies - fascism | 76 | 6_speak_never_bombarded_lies | |
| | | 7 | gates - philanthrocapitalism - depopulate - vaccine - provera | 70 | 7_gates_philanthrocapitalism_depopulate_vaccine | |
| | | 8 | robots - humanoid - transhumanism - microchip - hackable | 68 | 8_robots_humanoid_transhumanism_microchip | |
| | | 9 | davos - soros - oligarchies - rockefeller - kennedy | 57 | 9_davos_soros_oligarchies_rockefeller | |
| | | 10 | afghanistan - zelensky - wars - libya - propaganda | 55 | 10_afghanistan_zelensky_wars_libya | |
| | | 11 | 5g - ghz - antennas - watts - alberta | 53 | 11_5g_ghz_antennas_watts | |
| | | 12 | decentralized - ecb - governments - cash - cryptos | 48 | 12_decentralized_ecb_governments_cash | |
| | | 13 | cure - carcinoma - cannabis - holistic - gcmaf | 48 | 13_cure_carcinoma_cannabis_holistic | |
| | | 14 | globalist - farmers - crisis - eating - sustainable | 48 | 14_globalist_farmers_crisis_eating | |
| | | 15 | growit - vegetables - tomatoes - seeds - peppers | 47 | 15_growit_vegetables_tomatoes_seeds | |
| | | 16 | transgender - gays - pornography - indoctrination - mothers | 33 | 16_transgender_gays_pornography_indoctrination | |
| | | 17 | fbi - whistleblower - syndicate - murdoch - google | 32 | 17_fbi_whistleblower_syndicate_murdoch | |
| | | 18 | trudeau - gofundme - censorship - protesters - convoy | 26 | 18_trudeau_gofundme_censorship_protesters | |
| | | 19 | cities - minute - surveillance - lockdown - technocratic | 24 | 19_cities_minute_surveillance_lockdown | |
| | | 20 | biometric - ccpchina - wechat - surveillance - qr | 22 | 20_biometric_ccpchina_wechat_surveillance | |
| | | 21 | pedophiles - trafficked - prostitution - scully - oligarchs | 22 | 21_pedophiles_trafficked_prostitution_scully | |
| | | 22 | greenpeace - climatologist - scaremongering - deniers - warms | 21 | 22_greenpeace_climatologist_scaremongering_deniers | |
| | | 23 | fluoridated - colgate - neurotoxicant - dumbing - hexafluorosilicic | 20 | 23_fluoridated_colgate_neurotoxicant_dumbing | |
| | |
| | </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 |
| | |
