Hugging Face's logo

AIDA-UPM
/
MARTINI_enrich_BERTopic_IntheboxWithJohnLawrence

Text Classification
BERTopic
Model card Files Community
MARTINI_enrich_BERTopic_IntheboxWithJohnLawrence
File size: 3,103 Bytes 
0ff3ba4
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
 

---
tags:
- bertopic
library_name: bertopic
pipeline_tag: text-classification
---

# MARTINI_enrich_BERTopic_IntheboxWithJohnLawrence

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("AIDA-UPM/MARTINI_enrich_BERTopic_IntheboxWithJohnLawrence")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 16
* Number of training documents: 1618

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | protest - england - gangs - bnp - migrants | 21 | -1_protest_england_gangs_bnp | 
| 0 | coronavirus - pfizer - vaccinated - muscaria - dna | 802 | 0_coronavirus_pfizer_vaccinated_muscaria | 
| 1 | antiwhite - britain - supremacy - christianity - persecuted | 120 | 1_antiwhite_britain_supremacy_christianity | 
| 2 | ukrainians - zelensky - russia - missiles - prigozhin | 118 | 2_ukrainians_zelensky_russia_missiles | 
| 3 | alek - bbc - yerbury - youtube - winners | 61 | 3_alek_bbc_yerbury_youtube | 
| 4 | refugees - reformuk - deported - rwanda - welcoming | 59 | 4_refugees_reformuk_deported_rwanda | 
| 5 | oldham - assaults - victim - arrested - mugger | 59 | 5_oldham_assaults_victim_arrested | 
| 6 | paedophiles - indoctrinated - transgender - instagram - fgm | 59 | 6_paedophiles_indoctrinated_transgender_instagram | 
| 7 | illegals - border - arrived - boats - england | 55 | 7_illegals_border_arrived_boats | 
| 8 | campaigning - oldham - nationalists - labour - ballot | 54 | 8_campaigning_oldham_nationalists_labour | 
| 9 | refugees - housed - landlords - nhpuk - telford | 47 | 9_refugees_housed_landlords_nhpuk | 
| 10 | rapist - assaulted - bradford - manchester - convicted | 40 | 10_rapist_assaulted_bradford_manchester | 
| 11 | murdered - stabbing - batley - shahid - jail | 39 | 11_murdered_stabbing_batley_shahid | 
| 12 | carmarthenshire - llanelli - hotel - stradey - patrioticalternative | 35 | 12_carmarthenshire_llanelli_hotel_stradey | 
| 13 | annecy - burqa - stabbed - guerilla - islamabad | 27 | 13_annecy_burqa_stabbed_guerilla | 
| 14 | nationalist - france - populists - parliament - ban | 22 | 14_nationalist_france_populists_parliament |
  
</details>

## 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: False
* zeroshot_min_similarity: 0.7
* zeroshot_topic_list: None

## Framework versions

* Numpy: 1.26.4
* HDBSCAN: 0.8.40
* UMAP: 0.5.7
* Pandas: 2.2.3
* Scikit-Learn: 1.5.2
* Sentence-transformers: 3.3.1
* Transformers: 4.46.3
* Numba: 0.60.0
* Plotly: 5.24.1
* Python: 3.10.12