Singapore_BERTopic
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("sneakykilli/Singapore_BERTopic")
topic_model.get_topic_info()
Topic overview
- Number of topics: 10
- Number of training documents: 160
Click here for an overview of all topics.
Topic ID | Topic Keywords | Topic Frequency | Label |
---|---|---|---|
-1 | airline - airlines - flights - refund - flight | 6 | -1_airline_airlines_flights_refund |
0 | airline - airlines - flights - singapore - meals | 31 | 0_airline_airlines_flights_singapore |
1 | refund - airline - airlines - complaint - singapore | 43 | 1_refund_airline_airlines_complaint |
2 | baggage - luggage - airlines - airline - bags | 20 | 2_baggage_luggage_airlines_airline |
3 | airlines - passengers - seats - flight - cabin | 14 | 3_airlines_passengers_seats_flight |
4 | refund - repayment - sia - customer - complaints | 11 | 4_refund_repayment_sia_customer |
5 | airlines - airline - fees - singapore - flights | 10 | 5_airlines_airline_fees_singapore |
6 | refund - airline - cancellation - booking - cancel | 9 | 6_refund_airline_cancellation_booking |
7 | miles - airlines - airline - mileage - loyalty | 9 | 7_miles_airlines_airline_mileage |
8 | airline - flight - reviews - booking - customer | 7 | 8_airline_flight_reviews_booking |
Training hyperparameters
- calculate_probabilities: False
- language: None
- low_memory: False
- min_topic_size: 5
- 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: 1.24.3
- HDBSCAN: 0.8.33
- UMAP: 0.5.5
- Pandas: 2.0.3
- Scikit-Learn: 1.2.2
- Sentence-transformers: 2.3.1
- Transformers: 4.36.2
- Numba: 0.57.1
- Plotly: 5.16.1
- Python: 3.10.12
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