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

# yelpreview_base

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("Ayomidedeji/yelpreview_base")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 98
* Number of training documents: 10000

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | food - good - place - great - like | 10 | -1_food_good_place_great | 
| 0 | mexican - tacos - salsa - burrito - food | 3827 | 0_mexican_tacos_salsa_burrito | 
| 1 | pizza - crust - pizzas - good - wait | 705 | 1_pizza_crust_pizzas_good | 
| 2 | bar - music - drinks - night - place | 393 | 2_bar_music_drinks_night | 
| 3 | burger - fries - burgers - good - like | 288 | 3_burger_fries_burgers_good | 
| 4 | ordered - just - bread - good - chicken | 275 | 4_ordered_just_bread_good | 
| 5 | sushi - roll - rolls - happy hour - happy | 261 | 5_sushi_roll_rolls_happy hour | 
| 6 | scottsdale - place - great - bar - food | 191 | 6_scottsdale_place_great_bar | 
| 7 | coffee - starbucks - coffee shop - shop - espresso | 190 | 7_coffee_starbucks_coffee shop_shop | 
| 8 | hotel - pool - room - stay - resort | 186 | 8_hotel_pool_room_stay | 
| 9 | minutes - table - server - asked - came | 183 | 9_minutes_table_server_asked | 
| 10 | chinese - chinese food - food - asian - china | 145 | 10_chinese_chinese food_food_asian | 
| 11 | thai - pad - curry - pad thai - thai food | 131 | 11_thai_pad_curry_pad thai | 
| 12 | beer - beers - peaks - brewery - craft | 131 | 12_beer_beers_peaks_brewery | 
| 13 | breakfast - eggs - pancakes - toast - french toast | 115 | 13_breakfast_eggs_pancakes_toast | 
| 14 | pho - vietnamese - spring rolls - spring - broth | 104 | 14_pho_vietnamese_spring rolls_spring | 
| 15 | bbq - brisket - ribs - sauce - pork | 94 | 15_bbq_brisket_ribs_sauce | 
| 16 | theater - movie - seats - movies - theaters | 84 | 16_theater_movie_seats_movies | 
| 17 | food - place - great - lunch - love | 82 | 17_food_place_great_lunch | 
| 18 | hair - cut - salon - haircut - barber | 81 | 18_hair_cut_salon_haircut | 
| 19 | great - valentine - food - patio - valentine day | 78 | 19_great_valentine_food_patio | 
| 20 | service - food - server - servers - food service | 71 | 20_service_food_server_servers | 
| 21 | clothes - shoes - store - nordstrom - pair | 69 | 21_clothes_shoes_store_nordstrom | 
| 22 | gym - classes - yoga - fitness - workout | 67 | 22_gym_classes_yoga_fitness | 
| 23 | phoenix - food - durant - restaurant - good | 66 | 23_phoenix_food_durant_restaurant | 
| 24 | italian - pasta - italian food - restaurant - best | 65 | 24_italian_pasta_italian food_restaurant | 
| 25 | sandwich - sandwiches - bread - sacks - al | 64 | 25_sandwich_sandwiches_bread_sacks | 
| 26 | airport - flight - terminal - sky harbor - harbor | 64 | 26_airport_flight_terminal_sky harbor | 
| 27 | yogurt - frozen yogurt - flavors - frozen - toppings | 64 | 27_yogurt_frozen yogurt_flavors_frozen | 
| 28 | nails - nail - manicure - pedicure - gel | 62 | 28_nails_nail_manicure_pedicure | 
| 29 | car - auto - warranty - repair - new | 61 | 29_car_auto_warranty_repair | 
| 30 | trail - hike - park - mountain - view | 60 | 30_trail_hike_park_mountain | 
| 31 | dr - doctor - office - care - doctors | 58 | 31_dr_doctor_office_care | 
| 32 | ice - ice cream - cream - flavors - custard | 56 | 32_ice_ice cream_cream_flavors | 
| 33 | cupcakes - cupcake - cake - frosting - sprinkles | 54 | 33_cupcakes_cupcake_cake_frosting | 
| 34 | wine - wines - total wine - daniel - bottle | 51 | 34_wine_wines_total wine_daniel | 
| 35 | vegan - vegetarian - meat - mock - green | 45 | 35_vegan_vegetarian_meat_mock | 
| 36 | stars - christopher - star - reason - pat | 45 | 36_stars_christopher_star_reason | 
| 37 | staff - love place - food - great - friendly | 45 | 37_staff_love place_food_great | 
| 38 | stadium - game - spring training - parking - spring | 44 | 38_stadium_game_spring training_parking | 
| 39 | sub - subway - subs - jimmy - sandwich | 44 | 39_sub_subway_subs_jimmy | 
| 40 | indian - indian food - buffet - india - masala | 43 | 40_indian_indian food_buffet_india | 
| 41 | museum - kids - art - exhibits - exhibit | 40 | 41_museum_kids_art_exhibits | 
| 42 | donuts - donut - dunkin - bosa - dunkin donuts | 40 | 42_donuts_donut_dunkin_bosa | 
| 43 | fez - yelp - yelp event - event - yoli | 39 | 43_fez_yelp_yelp event_event | 
| 44 | vet - dog - animals - pet - dogs | 35 | 44_vet_dog_animals_pet | 
| 45 | happy hour - happy - hour - great happy - great | 35 | 45_happy hour_happy_hour_great happy | 
| 46 | steak - steaks - steakhouse - good steak - sides | 34 | 46_steak_steaks_steakhouse_good steak | 
| 47 | mall - stores - malls - shopping - food court | 33 | 47_mall_stores_malls_shopping | 
| 48 | phone - store - iphone - camera - customer | 33 | 48_phone_store_iphone_camera | 
| 49 | massage - spa - therapist - room - massages | 33 | 49_massage_spa_therapist_room | 
| 50 | dog - dogs - hot dog - hot - beef | 33 | 50_dog_dogs_hot dog_hot | 
| 51 | dog - pet - dog food - treats - pets | 32 | 51_dog_pet_dog food_treats | 
| 52 | closed - location closed - open - closed good - business closed | 29 | 52_closed_location closed_open_closed good | 
| 53 | dentist - dr - dental - teeth - office | 29 | 53_dentist_dr_dental_teeth | 
| 54 | salad - lunch - sandwich - chicken - dressing | 29 | 54_salad_lunch_sandwich_chicken | 
| 55 | greek - greek food - pita - gyro - greek restaurant | 27 | 55_greek_greek food_pita_gyro | 
| 56 | waffles - lo - chicken waffles - chicken - lolo | 27 | 56_waffles_lo_chicken waffles_chicken | 
| 57 | car - wash - car wash - job - exterior | 27 | 57_car_wash_car wash_job | 
| 58 | gelato - angel sweet - angel - italy - flavors | 27 | 58_gelato_angel sweet_angel_italy | 
| 59 | wings - wing - love wings - wild wings - buffalo | 26 | 59_wings_wing_love wings_wild wings | 
| 60 | tea - boba - teas - drink - milk tea | 25 | 60_tea_boba_teas_drink | 
| 61 | food - service - great food - great - awesome food | 25 | 61_food_service_great food_great | 
| 62 | bagel - bagels - cream cheese - lox - cream | 25 | 62_bagel_bagels_cream cheese_lox | 
| 63 | bruschetta - postino - wine - postinos - bottle | 24 | 63_bruschetta_postino_wine_postinos | 
| 64 | review - stars - reviews - hotdog - mold | 24 | 64_review_stars_reviews_hotdog | 
| 65 | foods - fresh easy - trader - easy - grocery | 22 | 65_foods_fresh easy_trader_easy | 
| 66 | mongolian - mongolian bbq - yc - bowl - bbq | 22 | 66_mongolian_mongolian bbq_yc_bowl | 
| 67 | service - food - time - horrible - ordered | 22 | 67_service_food_time_horrible | 
| 68 | course - holes - courses - played - tee | 21 | 68_course_holes_courses_played | 
| 69 | dog - dogs - park - dog park - active | 21 | 69_dog_dogs_park_dog park | 
| 70 | books - book - library - bookstore - used books | 21 | 70_books_book_library_bookstore | 
| 71 | pita - pita jungle - jungle - hummus - lentil | 20 | 71_pita_pita jungle_jungle_hummus | 
| 72 | pasta - spaghetti - sauce - italian - bread | 20 | 72_pasta_spaghetti_sauce_italian | 
| 73 | store - office max - prices - max - office | 20 | 73_store_office max_prices_max | 
| 74 | expensive - good price - food - price - good food | 19 | 74_expensive_good price_food_price | 
| 75 | thrift - store - goodwill - thrift store - vintage | 19 | 75_thrift_store_goodwill_thrift store | 
| 76 | safeway - store - grocery - shopping - winco | 19 | 76_safeway_store_grocery_shopping | 
| 77 | beer - bar - asked - minutes - trout | 18 | 77_beer_bar_asked_minutes | 
| 78 | japanese - tokyo - japanese food - knife - knives | 18 | 78_japanese_tokyo_japanese food_knife | 
| 79 | irish - pub - irish pub - fish chips - guinness | 16 | 79_irish_pub_irish pub_fish chips | 
| 80 | works meh - friendly awesome - ing great - awesome intense - job super | 16 | 80_works meh_friendly awesome_ing great_awesome intense | 
| 81 | zia - record - cd - stinkweeds - music | 15 | 81_zia_record_cd_stinkweeds | 
| 82 | tires - tire - discount tire - discount - new tires | 14 | 82_tires_tire_discount tire_discount | 
| 83 | cheesesteak - wiz - cheesesteaks - forefathers - philly | 14 | 83_cheesesteak_wiz_cheesesteaks_forefathers | 
| 84 | korean - korean food - kimchi - bbq - dishes | 14 | 84_korean_korean food_kimchi_bbq | 
| 85 | buffet - buffets - sushi - hong - hong kong | 13 | 85_buffet_buffets_sushi_hong | 
| 86 | gyro - tzatziki - pita - gyros - meat | 13 | 86_gyro_tzatziki_pita_gyros | 
| 87 | classes - campus - school - teacher - students | 13 | 87_classes_campus_school_teacher | 
| 88 | romantic - love love - whinings excellent - whinings - live amazing | 13 | 88_romantic_love love_whinings excellent_whinings | 
| 89 | patio - service - excellent service - excellent - great service | 12 | 89_patio_service_excellent service_excellent | 
| 90 | staff - clean staff - clean - selection awesome - friendly | 12 | 90_staff_clean staff_clean_selection awesome | 
| 91 | lux - coffee - espresso - love space - surfing | 12 | 91_lux_coffee_espresso_love space | 
| 92 | wine - bottle - glass - bar - maybe | 12 | 92_wine_bottle_glass_bar | 
| 93 | sushi - roll - ra - sushi bar - seated | 12 | 93_sushi_roll_ra_sushi bar | 
| 94 | german - schnitzel - murphy - german food - haus | 12 | 94_german_schnitzel_murphy_german food | 
| 95 | ethiopian - lalibela - injera - watt - lentils | 11 | 95_ethiopian_lalibela_injera_watt | 
| 96 | store - items - michaels - susan - employee | 11 | 96_store_items_michaels_susan |
  
</details>

## Training hyperparameters

* calculate_probabilities: True
* language: english
* 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: 1.25.2
* HDBSCAN: 0.8.36
* UMAP: 0.5.6
* Pandas: 2.0.3
* Scikit-Learn: 1.2.2
* Sentence-transformers: 3.0.0
* Transformers: 4.41.1
* Numba: 0.58.1
* Plotly: 5.15.0
* Python: 3.10.12
