| |
|
| | --- |
| | tags: |
| | - bertopic |
| | library_name: bertopic |
| | pipeline_tag: text-classification |
| | --- |
| | |
| | # MARTINI_enrich_BERTopic_Rus_truth |
| |
|
| | 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_Rus_truth") |
| | |
| | topic_model.get_topic_info() |
| | ``` |
| |
|
| | ## Topic overview |
| |
|
| | * Number of topics: 9 |
| | * Number of training documents: 995 |
| |
|
| | <details> |
| | <summary>Click here for an overview of all topics.</summary> |
| | |
| | | Topic ID | Topic Keywords | Topic Frequency | Label | |
| | |----------|----------------|-----------------|-------| |
| | | -1 | donetsk - zakharova - sanctions - mercenaries - nazi | 23 | -1_donetsk_zakharova_sanctions_mercenaries | |
| | | 0 | mariupol - azov - missiles - evacuated - battalion | 604 | 0_mariupol_azov_missiles_evacuated | |
| | | 1 | gazprombank - sanctions - euros - vladimir - poland | 141 | 1_gazprombank_sanctions_euros_vladimir | |
| | | 2 | zelensky - volodymyr - scholz - slovakia - suzdaltsev | 73 | 2_zelensky_volodymyr_scholz_slovakia | |
| | | 3 | kharkov - biolaboratories - pentagon - outbreak - borisovna | 37 | 3_kharkov_biolaboratories_pentagon_outbreak | |
| | | 4 | beijing - taiwan - ambassador - zhang - sino | 36 | 4_beijing_taiwan_ambassador_zhang | |
| | | 5 | marchers - nazis - victory - ivanovo - slovakia | 29 | 5_marchers_nazis_victory_ivanovo | |
| | | 6 | lavrov - sanctions - kissinger - baltic - aggressors | 28 | 6_lavrov_sanctions_kissinger_baltic | |
| | | 7 | missiles - howitzers - raytheon - supplied - cnn | 24 | 7_missiles_howitzers_raytheon_supplied | |
| | |
| | </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 |
| | |
