| |
|
| | --- |
| | tags: |
| | - bertopic |
| | library_name: bertopic |
| | pipeline_tag: text-classification |
| | --- |
| | |
| | # TopicModel_StoreReviews |
| | |
| | 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("shantanudave/TopicModel_StoreReviews") |
| | |
| | topic_model.get_topic_info() |
| | ``` |
| | |
| | ## Topic overview |
| | |
| | * Number of topics: 10 |
| | * Number of training documents: 14747 |
| | |
| | <details> |
| | <summary>Click here for an overview of all topics.</summary> |
| | |
| | | Topic ID | Topic Keywords | Topic Frequency | Label | |
| | |----------|----------------|-----------------|-------| |
| | | 0 | clothing - clothes - fashion - clothe - clothing store | 2672 | Fashionable Clothing Selection | |
| | | 1 | shopping - shop - price - cheap - store | 1864 | Diverse Shopping Experiences | |
| | | 2 | tidy - clean - branch - range - renovation | 1807 | Clean Retail Space | |
| | | 3 | quality - offer - use - stop - good | 1793 | Quality Offer Search | |
| | | 4 | selection - choice - large - large selection - size | 1459 | Large Size Selection | |
| | | 5 | advice - saleswoman - service - friendly - competent | 1447 | Friendly Saleswoman Service | |
| | | 6 | staff - friendly staff - staff staff - staff friendly - friendly | 1177 | Friendly Staff Selection | |
| | | 7 | wow - waw - oh - yeah - | 1108 | Expressive Words Discovery | |
| | | 8 | voucher - money - return - exchange - cash | 933 | Customer Return Experience | |
| | | 9 | super - friendly super - super friendly - pleasure - super service | 487 | super friendly service | |
| | |
| | </details> |
| | |
| | ## Training hyperparameters |
| | |
| | * calculate_probabilities: True |
| | * language: None |
| | * low_memory: False |
| | * min_topic_size: 10 |
| | * n_gram_range: (1, 1) |
| | * nr_topics: None |
| | * seed_topic_list: None |
| | * top_n_words: 10 |
| | * verbose: True |
| | * zeroshot_min_similarity: 0.7 |
| | * zeroshot_topic_list: None |
| | |
| | ## Framework versions |
| | |
| | * Numpy: 1.23.5 |
| | * HDBSCAN: 0.8.33 |
| | * UMAP: 0.5.5 |
| | * Pandas: 1.3.5 |
| | * Scikit-Learn: 1.4.1.post1 |
| | * Sentence-transformers: 2.6.1 |
| | * Transformers: 4.39.3 |
| | * Numba: 0.59.1 |
| | * Plotly: 5.21.0 |
| | * Python: 3.10.13 |
| | |
