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--- |
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tags: |
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- bertopic |
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library_name: bertopic |
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pipeline_tag: text-classification |
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--- |
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# MARTINI_enrich_BERTopic_TruthIsStillHateSpeech |
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This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model. |
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BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets. |
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## Usage |
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To use this model, please install BERTopic: |
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``` |
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pip install -U bertopic |
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``` |
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You can use the model as follows: |
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```python |
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from bertopic import BERTopic |
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topic_model = BERTopic.load("AIDA-UPM/MARTINI_enrich_BERTopic_TruthIsStillHateSpeech") |
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topic_model.get_topic_info() |
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``` |
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## Topic overview |
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* Number of topics: 10 |
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* Number of training documents: 820 |
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<details> |
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<summary>Click here for an overview of all topics.</summary> |
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| Topic ID | Topic Keywords | Topic Frequency | Label | |
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|----------|----------------|-----------------|-------| |
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| -1 | jews - whites - racist - diversity - russia | 20 | -1_jews_whites_racist_diversity | |
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| 0 | antisemitism - jew - mossad - lbj - victims | 418 | 0_antisemitism_jew_mossad_lbj | |
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| 1 | racism - whites - supremacy - globohomo - republican | 87 | 1_racism_whites_supremacy_globohomo | |
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| 2 | lgbtq - pedophile - fundamentalism - california - satanic | 73 | 2_lgbtq_pedophile_fundamentalism_california | |
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| 3 | technocracy - vaxxed - plandemic - conspiracy - china | 57 | 3_technocracy_vaxxed_plandemic_conspiracy | |
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| 4 | britons - whites - colonisation - wales - populations | 45 | 4_britons_whites_colonisation_wales | |
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| 5 | rapist - muslims - riots - abused - leicester | 38 | 5_rapist_muslims_riots_abused | |
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| 6 | zelenskyy - ukrainians - crimea - volodymyr - holocaust | 34 | 6_zelenskyy_ukrainians_crimea_volodymyr | |
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| 7 | hitler - nationalsozialistiche - comrades - 1936 - chapter | 24 | 7_hitler_nationalsozialistiche_comrades_1936 | |
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| 8 | zionist - refugees - jewry - multiculturalism - hias | 24 | 8_zionist_refugees_jewry_multiculturalism | |
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</details> |
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## Training hyperparameters |
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* calculate_probabilities: True |
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* language: None |
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* low_memory: False |
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* min_topic_size: 10 |
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* n_gram_range: (1, 1) |
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* nr_topics: None |
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* seed_topic_list: None |
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* top_n_words: 10 |
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* verbose: False |
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* zeroshot_min_similarity: 0.7 |
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* zeroshot_topic_list: None |
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## Framework versions |
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* Numpy: 1.26.4 |
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* HDBSCAN: 0.8.40 |
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* UMAP: 0.5.7 |
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* Pandas: 2.2.3 |
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* Scikit-Learn: 1.5.2 |
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* Sentence-transformers: 3.3.1 |
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* Transformers: 4.46.3 |
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* Numba: 0.60.0 |
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* Plotly: 5.24.1 |
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* Python: 3.10.12 |
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