BERTopic_june30
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("shantanudave/BERTopic_june30")
topic_model.get_topic_info()
Topic overview
- Number of topics: 18
- Number of training documents: 8526
Click here for an overview of all topics.
Topic ID | Topic Keywords | Topic Frequency | Label |
---|---|---|---|
0 | payment - pay - card - bank - money | 742 | Payment Issues Detection |
1 | load - slow - search - article - doesnt | 705 | Slow Search Function |
2 | clothes - clothing - size - fashion - large size | 683 | Large Size Quality Clothing |
3 | bon - - - - | 668 | bon documents collection |
4 | clear - intuitive - clear easy - recommend - selection | 665 | Easy Clear Navigation |
5 | - - - - | 649 | Keyword-Driven Document Analysis |
6 | shopping - staff - friendly - store - satisfy | 578 | Friendly staff satisfaction |
7 | delivery - fast delivery - fast - shipping - ship | 563 | Fast Delivery Quality |
8 | cart - shop cart - log - password - add | 548 | Shopping Cart Issues |
9 | easy use - easy - use - use easy - quick easy | 531 | Quick & Easy Solutions |
10 | awesome - excellent - think - clearly - phenomenal | 462 | Really Phenomenal Clear Thinking |
11 | quality - price - quality quality - price quality - comfortable | 454 | Excellent Quality Price |
12 | work work - work - work quickly - flawlessly - work flawlessly | 390 | Efficient Flawless Work |
13 | super super - super - superb - superb super - super friendly | 349 | Superb Friendly Coat |
14 | really simple - ra - solve problem - control - satisfied easy | 145 | User-Friendly Problem Solver |
15 | clear clear - clear - fast clear - clear fast - super clear | 144 | Clear and Transparent Working |
16 | discover - stuff good - stuff - fact - clearly | 129 | Discovering Interesting Facts |
17 | satisfied - satisfaction - totally satisfied - satisfied good - completely satisfied | 121 | Utmost Satisfaction |
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: 4.41.2
- Numba: 0.59.1
- Plotly: 5.22.0
- Python: 3.10.13
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