| tags: | |
| - bertopic | |
| library_name: bertopic | |
| pipeline_tag: text-classification | |
| # Bertopic_Keybert_Champions | |
| 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("Noibu/Bertopic_Keybert_Champions") | |
| topic_model.get_topic_info() | |
| ``` | |
| ## Topic overview | |
| * Number of topics: 10 | |
| * Number of training documents: 11678 | |
| <details> | |
| <summary>Click here for an overview of all topics.</summary> | |
| | Topic ID | Topic Keywords | Topic Frequency | Label | | |
| |----------|----------------|-----------------|-------| | |
| | -1 | short - powerblend - mesh short - shorts - big tall | 78 | -1_short_powerblend_mesh short_shorts | | |
| | 0 | ny - york - new york - st - st apt | 2099 | 0_ny_york_new york_st | | |
| | 1 | available color - color - color black - grey - white | 5852 | 1_available color_color_color black_grey | | |
| | 2 | search result - search - short search - item search - pant search | 2210 | 2_search result_search_short search_item search | | |
| | 3 | address close - shipping address - address - shipping - michael | 463 | 3_address close_shipping address_address_shipping | | |
| | 4 | size xl - size guide - xl xl - xl available - xl | 403 | 4_size xl_size guide_xl xl_xl available | | |
| | 5 | code - code order - apply - new premium - premium | 190 | 5_code_code order_apply_new premium | | |
| | 6 | password - new password - login - account - enter | 140 | 6_password_new password_login_account | | |
| | 7 | shipping address - address address - address - address order - new address | 131 | 7_shipping address_address address_address_address order | | |
| | 8 | billing - credit card - card number - card - credit | 112 | 8_billing_credit card_card number_card | | |
| </details> | |
| ## Training hyperparameters | |
| * calculate_probabilities: True | |
| * language: None | |
| * low_memory: False | |
| * min_topic_size: 50 | |
| * n_gram_range: (1, 2) | |
| * nr_topics: 10 | |
| * seed_topic_list: [['ship', 'address', 'location', 'destination', 'post', 'deliver', 'florida', 'texas', 'united states', 'europe', 'asia'], ['password', 'account', 'login', 'sign in', 'email', 'id', 'authentication', 'username'], ['select', 'choose', 'sort', 'next', 'more', 'back', 'scroll', 'previous', 'search', 'results', 'catalog', 'find', 'lookup', 'query', 'browse', 'explore', 'filter'], ['first', 'last', 'name', 'username', 'middlename', 'surname', 'given name', 'alias'], ['cart', 'basket', 'bag', 'add', 'remove', 'edit', 'cancel', 'update', 'delete', 'modify', 'change'], ['checkout', 'payment', 'pay', 'order', 'purchase', 'billing', 'transaction'], ['small', 'medium', 'large', 'extra large', 's', 'm', 'l', 'xl', 'xxl', 'slim fit', 'size', 'fit', 'quantity'], ['promo', 'code', 'apply', 'welcome', 'offer']] | |
| * top_n_words: 10 | |
| * verbose: False | |
| ## Framework versions | |
| * Numpy: 1.23.5 | |
| * HDBSCAN: 0.8.33 | |
| * UMAP: 0.5.3 | |
| * Pandas: 1.5.3 | |
| * Scikit-Learn: 1.2.2 | |
| * Sentence-transformers: 2.2.2 | |
| * Transformers: 4.31.0 | |
| * Numba: 0.56.4 | |
| * Plotly: 5.15.0 | |
| * Python: 3.10.12 | |