
# transformers_reservednature_topic

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("nsugianto/transformers_reservednature_topic")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 9
* Number of training documents: 348

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | sea - beach - grey - mark - off | 37 | -1_sea_beach_grey_mark | 
| 0 | manta - mantas - mantaenjoy - rays - ray | 76 | 0_manta_mantas_mantaenjoy_rays | 
| 1 | alpha - turtle - turtles - octopus - shot | 14 | 1_alpha_turtle_turtles_octopus | 
| 2 | shark - sharks - sharky - leopard - leopards | 23 | 2_shark_sharks_sharky_leopard | 
| 3 | julian - rocks - stone - snorkel - snorkeling | 58 | 3_julian_rocks_stone_snorkel | 
| 4 | photo - unsplash - pic - view - via | 40 | 4_photo_unsplash_pic_view | 
| 5 | byron - bay - beach - shore - snorkelling | 15 | 5_byron_bay_beach_shore | 
| 6 | weekend - fran - friday - happy - thanks | 58 | 6_weekend_fran_friday_happy | 
| 7 | mustard - kohls - sandwich - morning - stain | 27 | 7_mustard_kohls_sandwich_morning |
  
</details>

## Training hyperparameters

* calculate_probabilities: False
* language: english
* low_memory: False
* min_topic_size: 10
* n_gram_range: (1, 1)
* nr_topics: 25
* 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

{"library_name": "bertopic", "tags": ["bertopic"], "pipeline_tag": "text-classification"}
bertopic text-classification region:us