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bertopic-test_3030

Text Classification
BERTopic
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bertopic-test_3030
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---
tags:
- bertopic
library_name: bertopic
pipeline_tag: text-classification
---

# bertopic-test_3030

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("ahessamb/bertopic-test_3030")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 30
* Number of training documents: 1570

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| 0 | apecoin - neckline - shoulders - fluctuating - chart | 2 | 0_apecoin_neckline_shoulders_fluctuating | 
| 1 | astra - letter - investors - coindesk - bankruptcy | 84 | 1_astra_letter_investors_coindesk | 
| 2 | 26 - bulls - rsi - ceiling - low | 30 | 2_26_bulls_rsi_ceiling | 
| 3 | mutant - mayc - bayc - club - nfts | 112 | 3_mutant_mayc_bayc_club | 
| 4 | shib - doge - shiba - sentiment - dogecoin | 115 | 4_shib_doge_shiba_sentiment | 
| 5 | xrp - btc - lawsuit - sleuth - bullish | 47 | 5_xrp_btc_lawsuit_sleuth | 
| 6 | binance - securities - crypto - coinbase - regulatory | 147 | 6_binance_securities_crypto_coinbase | 
| 7 | ordibots - ordinals - collection - gbrc721 - text | 33 | 7_ordibots_ordinals_collection_gbrc721 | 
| 8 | kitao - sbi - xrp - ripple - holdings | 95 | 8_kitao_sbi_xrp_ripple | 
| 9 | listings - exponential - coin - ethereum - defi | 163 | 9_listings_exponential_coin_ethereum | 
| 10 | yuan - event - games - rewards - olympics | 68 | 10_yuan_event_games_rewards | 
| 11 | emptydoc - richmond - fashion - shiba - community | 15 | 11_emptydoc_richmond_fashion_shiba | 
| 12 | sygnum - crypto - piggy - btr - huobi | 59 | 12_sygnum_crypto_piggy_btr | 
| 13 | dln - debridge - chains - liquidity - slippage | 3 | 13_dln_debridge_chains_liquidity | 
| 14 | longitude - chronometer - bitcoin - ships - rogers | 5 | 14_longitude_chronometer_bitcoin_ships | 
| 15 | arbitrum - airdrop - recipients - scalability - ethereum | 14 | 15_arbitrum_airdrop_recipients_scalability | 
| 16 | ethereum - fidelity - blackrock - cryptocurrency - fee | 111 | 16_ethereum_fidelity_blackrock_cryptocurrency | 
| 17 | swyftx - shibarium - token - shiba - shibaswap | 17 | 17_swyftx_shibarium_token_shiba | 
| 18 | zachxbt - squid - huang - donation - accused | 21 | 18_zachxbt_squid_huang_donation | 
| 19 | reading - trend - leaning - ltc - breakdown | 2 | 19_reading_trend_leaning_ltc | 
| 20 | tether - reserve - gusd - cbdcs - bills | 45 | 20_tether_reserve_gusd_cbdcs | 
| 21 | lace - brave - mobile - wallet - iog | 2 | 21_lace_brave_mobile_wallet | 
| 22 | binance - day - coinbase - exchange - bitcoin | 82 | 22_binance_day_coinbase_exchange | 
| 23 | v3 - bnb - repurchase - peng - pancakeswap | 2 | 23_v3_bnb_repurchase_peng | 
| 24 | xrp - banks - ripple - institutions - p2p | 6 | 24_xrp_banks_ripple_institutions | 
| 25 | ada - level - litecoin - cardano - resistance | 186 | 25_ada_level_litecoin_cardano | 
| 26 | xrp - hoskinson - cardano - securities - analisa | 26 | 26_xrp_hoskinson_cardano_securities | 
| 27 | peaq - lunc - fetch - cosmos - terra | 73 | 27_peaq_lunc_fetch_cosmos | 
| 28 | kostin - russia - sanctions - currency - yuan | 2 | 28_kostin_russia_sanctions_currency | 
| 29 | upgrade - terra - lunc - chrome - jumps | 3 | 29_upgrade_terra_lunc_chrome |
  
</details>

## Training hyperparameters

* calculate_probabilities: False
* 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

## Framework versions

* Numpy: 1.22.4
* HDBSCAN: 0.8.29
* UMAP: 0.5.3
* Pandas: 1.5.3
* Scikit-Learn: 1.2.2
* Sentence-transformers: 2.2.2
* Transformers: 4.30.2
* Numba: 0.56.4
* Plotly: 5.13.1
* Python: 3.10.12