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pszemraj/BERTopic-summcomparer-gauntlet-v0p1-all-roberta-large-v1-document_text

sourceHugging Faceapache-2.0updated 9mo agoView on Hugging Face

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Model Card

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

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.

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Usage

To use this model, please install BERTopic:

pip install -U bertopic safetensors

You can use the model as follows:

python

from bertopic import BERTopic
topic_model = BERTopic.load("pszemraj/BERTopic-summcomparer-gauntlet-v0p1-all-roberta-large-v1-document_text")

topic_model.get_topic_info()

Topic overview

—Number of topics: 17
—Number of training documents: 995

<details> <summary>Click here for an overview of all topics.</summary>

Topic ID	Topic Keywords	Topic Frequency	Label
-1	clustering - convolutional - neural - hierarchical - autoregressive	11	-1clusteringconvolutionalneuralhierarchical
0	betty - door - her - gillis - room	15	0bettydoorhergillis
1	frozen - anna - snow - hans - elsa	241	1frozenannasnowhans
2	closeup - shot - viewpoint - umpire - camera	211	2closeupshotviewpointumpire
3	dory - gill - coral - marlin - ocean	171	3dorygillcoralmarlin
4	operations - structure - operation - theory - interpretation	60	4operationsstructureoperationtheory
5	spatial - identity - movement - identities - noir	59	5spatialidentitymovementidentities
6	vocabulary - words - topic - text - topics	45	6vocabularywordstopictext
7	encoder - captions - embeddings - decoder - caption	40	7encodercaptionsembeddingsdecoder
8	saw - hounds - smiled - had - hunt	26	8sawhoundssmiledhad
9	learning - assignment - data - research - project	22	9learningassignmentdataresearch
10	cogvideo - videos - videogpt - video - clips	21	10cogvideovideosvideogptvideo
11	lstm - recurrent - encoder - seq2seq - neural	18	11lstmrecurrentencoderseq2seq
12	improve - next - do - going - good	17	12improvenextdogoing
13	vocoding - spectrogram - enhancement - melspectrogram - audio	14	13vocodingspectrogramenhancementmelspectrogram
14	probabilities - tagging - probability - words - gram	12	14probabilitiestaggingprobabilitywords
15	convolutional - segmentation - superpixel - convolutions - superpixels	12	15convolutionalsegmentationsuperpixelconvolutions

</details>

hierarchy

Training hyperparameters

—calculate_probabilities: True
—language: None
—low_memory: False
—mintopicsize: 10
—ngramrange: (1, 1)
—nr_topics: None
—seedtopiclist: None
—topnwords: 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