
# 1M_bert

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("Jellywibble/1M_bert")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 20
* Number of training documents: 1000000

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| 0 | you - the - to - user - bot | 201385 | 0_you_the_to_user | 
| 1 | his - he - you - your - bot | 182561 | 1_his_he_you_your | 
| 2 | her - she - you - to - user | 99643 | 2_her_she_you_to | 
| 3 | his - he - you - to - the | 97803 | 3_his_he_you_to | 
| 4 | her - she - you - user - your | 55073 | 4_her_she_you_user | 
| 5 | his - he - you - to - the | 49339 | 5_his_he_you_to | 
| 6 | her - she - to - the - you | 48030 | 6_her_she_to_the | 
| 7 | his - he - you - the - to | 46294 | 7_his_he_you_the | 
| 8 | the - you - to - and - user | 40228 | 8_the_you_to_and | 
| 9 | his - he - you - the - to | 35152 | 9_his_he_you_the | 
| 10 | his - he - you - to - the | 23293 | 10_his_he_you_to | 
| 11 | his - he - you - the - to | 23158 | 11_his_he_you_the | 
| 12 | you - hoshi - to - her - the | 18615 | 12_you_hoshi_to_her | 
| 13 | his - jack - he - elijah - you | 16377 | 13_his_jack_he_elijah | 
| 14 | his - he - you - the - to | 12291 | 14_his_he_you_the | 
| 15 | tom - his - he - you - to | 11575 | 15_tom_his_he_you | 
| 16 | his - he - max - you - the | 11396 | 16_his_he_max_you | 
| 17 | liam - damien - he - his - you | 9937 | 17_liam_damien_he_his | 
| 18 | felix - his - he - the - you | 9730 | 18_felix_his_he_the | 
| 19 | ghost - his - he - you - the | 8120 | 19_ghost_his_he_you |
  
</details>

## Training hyperparameters

* calculate_probabilities: False
* language: multilingual
* 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: 1.23.1
* HDBSCAN: 0.8.33
* UMAP: 0.5.5
* Pandas: 1.3.5
* Scikit-Learn: 1.3.2
* Sentence-transformers: 2.3.1
* Transformers: 4.37.2
* Numba: 0.58.1
* Plotly: 5.19.0
* Python: 3.8.10

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