metadata
tags:
- bertopic
library_name: bertopic
pipeline_tag: text-classification
Qatar_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/Qatar_BERTopic")
topic_model.get_topic_info()
Topic overview
- Number of topics: 22
- Number of training documents: 714
Click here for an overview of all topics.
| 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 |
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