|
|
| --- |
| tags: |
| - bertopic |
| library_name: bertopic |
| pipeline_tag: text-classification |
| --- |
| |
| # Qatar_BERTopic |
| |
| This is a [BERTopic](https://github.com/MaartenGr/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("sneakykilli/Qatar_BERTopic") |
| |
| topic_model.get_topic_info() |
| ``` |
| |
| ## Topic overview |
| |
| * Number of topics: 22 |
| * Number of training documents: 714 |
| |
| <details> |
| <summary>Click here for an overview of all topics.</summary> |
| |
| | Topic ID | Topic Keywords | Topic Frequency | Label | |
| |----------|----------------|-----------------|-------| |
| | -1 | doha - qatar - airline - airlines - refund | 5 | -1_doha_qatar_airline_airlines | |
| | 0 | doha - qatar - airline - airlines - flights | 211 | 0_doha_qatar_airline_airlines | |
| | 1 | refund - refunded - refunds - booking - voucher | 78 | 1_refund_refunded_refunds_booking | |
| | 2 | doha - qatar - baggage - luggage - airline | 72 | 2_doha_qatar_baggage_luggage | |
| | 3 | airline - passengers - flights - attendant - steward | 49 | 3_airline_passengers_flights_attendant | |
| | 4 | qatar - airline - airlines - flights - carriers | 44 | 4_qatar_airline_airlines_flights | |
| | 5 | baggage - doha - airlines - airline - luggage | 39 | 5_baggage_doha_airlines_airline | |
| | 6 | airline - airlines - flights - emirates - flight | 35 | 6_airline_airlines_flights_emirates | |
| | 7 | refund - airline - flights - flight - cancel | 32 | 7_refund_airline_flights_flight | |
| | 8 | airline - airlines - seats - qatar - seating | 28 | 8_airline_airlines_seats_qatar | |
| | 9 | qatar - doha - airlines - flights - emirates | 18 | 9_qatar_doha_airlines_flights | |
| | 10 | customer - complaints - service - terrible - horrible | 17 | 10_customer_complaints_service_terrible | |
| | 11 | qatar - complaint - doha - complaints - airline | 15 | 11_qatar_complaint_doha_complaints | |
| | 12 | avios - qatar - booking - compensation - aviso | 14 | 12_avios_qatar_booking_compensation | |
| | 13 | airline - airlines - flight - airplane - horrible | 9 | 13_airline_airlines_flight_airplane | |
| | 14 | doha - qatar - flights - cancellation - airlines | 8 | 14_doha_qatar_flights_cancellation | |
| | 15 | doha - qatar - qatari - emirates - flight | 8 | 15_doha_qatar_qatari_emirates | |
| | 16 | doha - qatar - airlines - bangkok - airport | 8 | 16_doha_qatar_airlines_bangkok | |
| | 17 | seats - seating - airline - booked - seat | 7 | 17_seats_seating_airline_booked | |
| | 18 | qatar - opodo - airline - refunded - voucher | 6 | 18_qatar_opodo_airline_refunded | |
| | 19 | doha - qatar - flight - destinations - airways | 6 | 19_doha_qatar_flight_destinations | |
| | 20 | qatar - airlines - disability - flight - wheelchair | 5 | 20_qatar_airlines_disability_flight | |
| |
| </details> |
| |
| ## 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 |
| |
