BERTopic-summcomparer-gauntlet-v0p1-all-roberta-large-v1-summary

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("pszemraj/BERTopic-summcomparer-gauntlet-v0p1-all-roberta-large-v1-summary")

topic_model.get_topic_info()

Topic overview

• Number of topics: 25
• Number of training documents: 1960

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
-1	question - it - going - they - she	11	-1_question_it_going_they
0	merging - merge - operations - concept - computation	62	0_merging_merge_operations_concept
1	rainsford - island - sailors - hunted - hunting	208	1_rainsford_island_sailors_hunted
2	film - films - noir - dissertation - cinema	116	2_film_films_noir_dissertation
3	patients - predicting - predict - prediction - unsupervised	114	3_patients_predicting_predict_prediction
4	cogvideo - videos - cogview2 - cog - pretrained	108	4_cogvideo_videos_cogview2_cog
5	frozen - sled - snow - princess - hans	108	5_frozen_sled_snow_princess
6	dory - coral - fish - gill - ocean	103	6_dory_coral_fish_gill
7	captions - encoder - image - images - caption	103	7_captions_encoder_image_images
8	law - assignments - lectures - assignment - learning	99	8_law_assignments_lectures_assignment
9	convolutional - segmentation - imaging - pathology - superpixels	98	9_convolutional_segmentation_imaging_pathology
10	enhancement - enhancing - vocoding - vocoder - audio	97	10_enhancement_enhancing_vocoding_vocoder
11	tokenization - medical - health - words - embeddings	97	11_tokenization_medical_health_words
12	gillis - scene - script - sunset - movie	93	12_gillis_scene_script_sunset
13	anthony - antony - scene - guy - his	92	13_anthony_antony_scene_guy
14	topic - projects - sociology - research - students	90	14_topic_projects_sociology_research
15	peter - conversation - asks - questions - cheesy	88	15_peter_conversation_asks_questions
16	sniper - marine - unarmed - combat - trained	86	16_sniper_marine_unarmed_combat
17	communication - apparatus - method - input - embodiment	68	17_communication_apparatus_method_input
18	words - phrases - political - unsupervised - topic	27	18_words_phrases_political_unsupervised
19	clustering - similarity - unsupervised - topic - plagiarism	23	19_clustering_similarity_unsupervised_topic
20	book - novel - father - read - arrives	21	20_book_novel_father_read
21	topic - loans - clustering - loan - analyze	19	21_topic_loans_clustering_loan
22	sciences - science - society - research - scientists	16	22_sciences_science_society_research
23	dynamics - situation - quantum - mechanics - note	13	23_dynamics_situation_quantum_mechanics

hierarchy

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: True

Framework versions

• Numpy: 1.22.4
• HDBSCAN: 0.8.29
• UMAP: 0.5.3
• Pandas: 1.5.3
• Scikit-Learn: 1.2.2
• Sentence-transformers: 2.2.2
• Transformers: 4.29.2
• Numba: 0.56.4
• Plotly: 5.13.1
• Python: 3.10.11