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Rain4301/
Reddit_BERTopic_MentalBERT

Name: Reddit_BERTopic_MentalBERT
Availability: InStock

bertopic

text-classification

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Reddit_BERTopic_MentalBERT

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:

python

from bertopic import BERTopic
topic_model = BERTopic.load("Rain4301/Reddit_BERTopic_MentalBERT")

topic_model.get_topic_info()

Topic overview

Number of topics: 7
Number of training documents: 500

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
-1	im - like - dont - feel - people	12	-1_im_like_dont_feel
0	im - like - anxiety - dont - feel	206	0_im_like_anxiety_dont
1	hesitant - uneasy - undecided - undecided uneasy - uneasy hesitant	108	1_hesitant_uneasy_undecided_undecided uneasy
2	im - like - feel - dont - know	72	2_im_like_feel_dont
3	therapy - therapist - help - like - please	45	3_therapy_therapist_help_like
4	nan - deleted - every time - nan deleted - time	40	4_nan_deleted_every time_nan deleted
5	im - proud - go - happy - congrats	17	5_im_proud_go_happy

Training hyperparameters

calculate_probabilities: False
language: None
low_memory: False
min_topic_size: 10
n_gram_range: (1, 3)
nr_topics: 7
seed_topic_list: None
top_n_words: 15
verbose: False
zeroshot_min_similarity: 0.7
zeroshot_topic_list: None

Framework versions

Numpy: 1.26.4
HDBSCAN: 0.8.40
UMAP: 0.5.9.post2
Pandas: 2.3.0
Scikit-Learn: 1.7.0
Sentence-transformers: 5.0.0
Transformers: 4.52.4
Numba: 0.61.2
Plotly: 6.2.0
Python: 3.11.13