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Singapore_BERTopic
sneakykilli/Singapore_BERTopic
Singapore_BERTopic is a text classification model from sneakykilli. Use it when you need a label for a piece of text. It is set up for 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.
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At a glance
- Task
- Text Classification
- Library
- bertopic
- Access
- Public
- Created
- Feb 7, 2024
- Updated
- Feb 7, 2024
- SHA
- 39220e8c
Try a prompt
Model card
From the Hugging Face model README
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
| 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
- Task
- Text Classification
- Library
- bertopic
- Created
- Feb 7, 2024
- Updated
- Feb 7, 2024