Reddit_BERTopic_MentalBERT
This is a 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:
from bertopic import BERTopic
topic_model = BERTopic.load("Rain4301/Reddit_BERTopic_MentalBERT")
topic_model.get_topic_info()
Topic overview
- Number of topics: 7
- Number of training documents: 500
Click here for an overview of all topics.
| Topic ID | Topic Keywords | Topic Frequency | Label |
|---|---|---|---|
| -1 | im - like - dont - feel - people | 12 | -1_im_like_dont_feel |
| 0 | im - like - anxiety - dont - feel | 206 | 0_im_like_anxiety_dont |
| 1 | hesitant - uneasy - undecided - undecided uneasy - uneasy hesitant | 108 | 1_hesitant_uneasy_undecided_undecided uneasy |
| 2 | im - like - feel - dont - know | 72 | 2_im_like_feel_dont |
| 3 | therapy - therapist - help - like - please | 45 | 3_therapy_therapist_help_like |
| 4 | nan - deleted - every time - nan deleted - time | 40 | 4_nan_deleted_every time_nan deleted |
| 5 | im - proud - go - happy - congrats | 17 | 5_im_proud_go_happy |
Training hyperparameters
- calculate_probabilities: False
- language: None
- low_memory: False
- min_topic_size: 10
- n_gram_range: (1, 3)
- nr_topics: 7
- seed_topic_list: None
- top_n_words: 15
- verbose: False
- zeroshot_min_similarity: 0.7
- zeroshot_topic_list: None
Framework versions
- Numpy: 1.26.4
- HDBSCAN: 0.8.40
- UMAP: 0.5.9.post2
- Pandas: 2.3.0
- Scikit-Learn: 1.7.0
- Sentence-transformers: 5.0.0
- Transformers: 4.52.4
- Numba: 0.61.2
- Plotly: 6.2.0
- Python: 3.11.13
- Downloads last month
- 5