urdu_news_topic_modeling
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("shaistaDev7/urdu_news_topic_modeling")
topic_model.get_topic_info()
Topic overview
- Number of topics: 7
- Number of training documents: 7991
Click here for an overview of all topics.
| Topic ID | Topic Keywords | Topic Frequency | Label |
|---|---|---|---|
| 0 | پولیو - ڈاکٹر - مہم - بتایا - صحت | 1626 | 0_پولیو_ڈاکٹر_مہم_بتایا |
| 1 | فلم - اداکارہ - اداکار - شادی - بالی | 1290 | 1_فلم_اداکارہ_اداکار_شادی |
| 2 | عمران - خان - تحریک - حکومت - لیگ | 1263 | 2_عمران_خان_تحریک_حکومت |
| 3 | روپے - مالی - ملین - سال - ڈالر | 1062 | 3_روپے_مالی_ملین_سال |
| 4 | فون - صارفین - ویوو - موبائل - بک | 928 | 4_فون_صارفین_ویوو_موبائل |
| 5 | ٹیم - میچ - کرکٹ - رنز - ٹورنامنٹ | 916 | 5_ٹیم_میچ_کرکٹ_رنز |
| 6 | کورونا - وائرس - کیسز - مریض - ہزار | 906 | 6_کورونا_وائرس_کیسز_مریض |
Training hyperparameters
- calculate_probabilities: True
- language: urdu
- low_memory: True
- 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: 1.5.3
- Scikit-Learn: 1.2.2
- Sentence-transformers: 2.2.2
- Transformers: 4.35.2
- Numba: 0.58.1
- Plotly: 5.15.0
- Python: 3.10.12
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