--- tags: - bertopic library_name: bertopic pipeline_tag: text-classification --- # MARTINI_enrich_BERTopic_uch_uch_uch 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_uch_uch_uch") topic_model.get_topic_info() ``` ## Topic overview * Number of topics: 11 * Number of training documents: 1648
Click here for an overview of all topics. | Topic ID | Topic Keywords | Topic Frequency | Label | |----------|----------------|-----------------|-------| | -1 | vakcinos - covid - 2021 - lietuva - euru | 21 | -1_vakcinos_covid_2021_lietuva | | 0 | vakcinacija - vaers - pfizer - koronaviruso - injekcijos | 1084 | 0_vakcinacija_vaers_pfizer_koronaviruso | | 1 | candida - bakteriju - insulino - produktus - hiperaktyviems | 120 | 1_candida_bakteriju_insulino_produktus | | 2 | baltarusija - ukrainai - zelenskio - rusijos - amerikieciai | 102 | 2_baltarusija_ukrainai_zelenskio_rusijos | | 3 | koronaviruso - pandemija - skaicius - imuniteta - dokumentas | 87 | 3_koronaviruso_pandemija_skaicius_imuniteta | | 4 | globalistu - nibiru - revoliucijas - pandemija - 2050 | 60 | 4_globalistu_nibiru_revoliucijas_pandemija | | 5 | kriptovaliutu - usd - rubli - rusija - banko | 53 | 5_kriptovaliutu_usd_rubli_rusija | | 6 | tepineliai - susitikimo - neegzistuojanciu - bukstauta - raportuokime | 40 | 6_tepineliai_susitikimo_neegzistuojanciu_bukstauta | | 7 | susitikimai - sunkiausias - mentalinio - plaukus - energijos | 36 | 7_susitikimai_sunkiausias_mentalinio_plaukus | | 8 | gmo - bioinzinerijos - crispr - patentas - pomidorai | 24 | 8_gmo_bioinzinerijos_crispr_patentas | | 9 | raskeviciau - konstitucija - ratifikavus - tolerancijos - bankiniai | 21 | 9_raskeviciau_konstitucija_ratifikavus_tolerancijos |
## 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