MARTINI_enrich_BERTopic_PlantBasedNews

This is a 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:

from bertopic import BERTopic
topic_model = BERTopic.load("AIDA-UPM/MARTINI_enrich_BERTopic_PlantBasedNews")

topic_model.get_topic_info()

Topic overview

• Number of topics: 14
• Number of training documents: 1270

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
-1	vegans - giveaway - farm - milk - cruelty	20	-1_vegans_giveaway_farm_milk
0	veganuary - podcast - harrisberg - cannibalism - diabetes	767	0_veganuary_podcast_harrisberg_cannibalism
1	lasagne - cauliflower - ginger - tofu - pancakes	91	1_lasagne_cauliflower_ginger_tofu
2	burgers - kfc - meatless - king - london	61	2_burgers_kfc_meatless_king
3	fats - keto - vegetables - cholesterol - brain	59	3_fats_keto_vegetables_cholesterol
4	deforestation - slaughterhouses - wildlife - agricultural - fao	51	4_deforestation_slaughterhouses_wildlife_agricultural
5	veganism - celebrities - miley - maggie - james	43	5_veganism_celebrities_miley_maggie
6	milks - challenge - free - today - dotsie	32	6_milks_challenge_free_today
7	christmas - tofurkey - stuffing - gingerbread - sainsburys	31	7_christmas_tofurkey_stuffing_gingerbread
8	fur - humane - petition - brexit - packham	27	8_fur_humane_petition_brexit
9	slaughterhouse - piglets - activists - rescued - picklesimer	27	9_slaughterhouse_piglets_activists_rescued
10	defra - meals - ireland - oxfordshire - earthshot	21	10_defra_meals_ireland_oxfordshire
11	climate - unicef - activists - aotearoa - newspaper	20	11_climate_unicef_activists_aotearoa
12	meatable - cells - cultured - fda - bacon	20	12_meatable_cells_cultured_fda

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