|
|
|
|
|
--- |
|
|
tags: |
|
|
- bertopic |
|
|
library_name: bertopic |
|
|
pipeline_tag: text-classification |
|
|
--- |
|
|
|
|
|
# urdu_news_topic_modeling |
|
|
|
|
|
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("shaistaDev7/urdu_news_topic_modeling") |
|
|
|
|
|
topic_model.get_topic_info() |
|
|
``` |
|
|
|
|
|
## Topic overview |
|
|
|
|
|
* Number of topics: 7 |
|
|
* Number of training documents: 7991 |
|
|
|
|
|
<details> |
|
|
<summary>Click here for an overview of all topics.</summary> |
|
|
|
|
|
| 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 | |
|
|
|
|
|
</details> |
|
|
|
|
|
## 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 |
|
|
|
