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--- |
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tags: |
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- bertopic |
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library_name: bertopic |
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pipeline_tag: text-classification |
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--- |
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# Singapore_BERTopic |
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This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model. |
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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 |
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To use this model, please install BERTopic: |
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``` |
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pip install -U bertopic |
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``` |
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You can use the model as follows: |
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```python |
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from bertopic import BERTopic |
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topic_model = BERTopic.load("sneakykilli/Singapore_BERTopic") |
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topic_model.get_topic_info() |
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``` |
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## Topic overview |
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* Number of topics: 10 |
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* Number of training documents: 160 |
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<details> |
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<summary>Click here for an overview of all topics.</summary> |
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| Topic ID | Topic Keywords | Topic Frequency | Label | |
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|----------|----------------|-----------------|-------| |
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| -1 | airline - airlines - flights - refund - flight | 6 | -1_airline_airlines_flights_refund | |
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| 0 | airline - airlines - flights - singapore - meals | 31 | 0_airline_airlines_flights_singapore | |
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| 1 | refund - airline - airlines - complaint - singapore | 43 | 1_refund_airline_airlines_complaint | |
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| 2 | baggage - luggage - airlines - airline - bags | 20 | 2_baggage_luggage_airlines_airline | |
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| 3 | airlines - passengers - seats - flight - cabin | 14 | 3_airlines_passengers_seats_flight | |
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| 4 | refund - repayment - sia - customer - complaints | 11 | 4_refund_repayment_sia_customer | |
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| 5 | airlines - airline - fees - singapore - flights | 10 | 5_airlines_airline_fees_singapore | |
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| 6 | refund - airline - cancellation - booking - cancel | 9 | 6_refund_airline_cancellation_booking | |
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| 7 | miles - airlines - airline - mileage - loyalty | 9 | 7_miles_airlines_airline_mileage | |
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| 8 | airline - flight - reviews - booking - customer | 7 | 8_airline_flight_reviews_booking | |
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</details> |
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## Training hyperparameters |
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* calculate_probabilities: False |
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* language: None |
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* low_memory: False |
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* min_topic_size: 5 |
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* n_gram_range: (1, 1) |
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* nr_topics: None |
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* seed_topic_list: None |
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* top_n_words: 10 |
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* verbose: False |
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* zeroshot_min_similarity: 0.7 |
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* zeroshot_topic_list: None |
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## Framework versions |
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* Numpy: 1.24.3 |
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* HDBSCAN: 0.8.33 |
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* UMAP: 0.5.5 |
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* Pandas: 2.0.3 |
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* Scikit-Learn: 1.2.2 |
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* Sentence-transformers: 2.3.1 |
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* Transformers: 4.36.2 |
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* Numba: 0.57.1 |
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* Plotly: 5.16.1 |
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* Python: 3.10.12 |
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