Add BERTopic model

README.md

@@ -0,0 +1,124 @@
+
+---
+tags:
+- bertopic
+library_name: bertopic
+pipeline_tag: text-classification
+---
+
+# cnn_dailymail_123_3000_1500_train
+
+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("KingKazma/cnn_dailymail_123_3000_1500_train")
+
+topic_model.get_topic_info()
+```
+
+## Topic overview
+
+* Number of topics: 57
+* Number of training documents: 3000
+
+<details>
+  <summary>Click here for an overview of all topics.</summary>
+  
+  | Topic ID | Topic Keywords | Topic Frequency | Label | 
+|----------|----------------|-----------------|-------| 
+| -1 | said - one - police - people - year | 10 | -1_said_one_police_people | 
+| 0 | league - player - cup - goal - game | 1070 | 0_league_player_cup_goal | 
+| 1 | police - said - home - murder - found | 320 | 1_police_said_home_murder | 
+| 2 | court - mr - said - year - sex | 142 | 2_court_mr_said_year | 
+| 3 | obama - president - republicans - house - republican | 113 | 3_obama_president_republicans_house | 
+| 4 | plane - flight - passenger - airport - aircraft | 89 | 4_plane_flight_passenger_airport | 
+| 5 | hospital - care - family - baby - mr | 59 | 5_hospital_care_family_baby | 
+| 6 | fashion - dress - style - look - collection | 57 | 6_fashion_dress_style_look | 
+| 7 | mr - minister - cameron - party - labour | 50 | 7_mr_minister_cameron_party | 
+| 8 | weight - diet - food - fat - school | 49 | 8_weight_diet_food_fat | 
+| 9 | mars - space - climate - nasa - mission | 43 | 9_mars_space_climate_nasa | 
+| 10 | apple - ipad - iphone - app - apples | 41 | 10_apple_ipad_iphone_app | 
+| 11 | shark - dolphin - fish - coast - water | 39 | 11_shark_dolphin_fish_coast | 
+| 12 | teacher - school - student - said - state | 37 | 12_teacher_school_student_said | 
+| 13 | murray - wimbledon - win - champion - match | 36 | 13_murray_wimbledon_win_champion | 
+| 14 | race - prix - hamilton - gold - world | 33 | 14_race_prix_hamilton_gold | 
+| 15 | dog - animal - owner - dogs - tiger | 32 | 15_dog_animal_owner_dogs | 
+| 16 | syrian - syria - isis - islamic - force | 32 | 16_syrian_syria_isis_islamic | 
+| 17 | storm - weather - lava - snow - said | 32 | 17_storm_weather_lava_snow | 
+| 18 | chocolate - sale - cent - online - caramel | 32 | 18_chocolate_sale_cent_online | 
+| 19 | afghanistan - afghan - pakistan - herat - taliban | 32 | 19_afghanistan_afghan_pakistan_herat | 
+| 20 | music - band - halen - song - album | 30 | 20_music_band_halen_song | 
+| 21 | beach - island - resort - park - hotel | 29 | 21_beach_island_resort_park | 
+| 22 | mcilroy - golf - round - shot - hole | 27 | 22_mcilroy_golf_round_shot | 
+| 23 | text - data - nsa - credit - email | 26 | 23_text_data_nsa_credit | 
+| 24 | show - film - movie - actor - griffiths | 26 | 24_show_film_movie_actor | 
+| 25 | putin - russian - russia - ukraine - moscow | 26 | 25_putin_russian_russia_ukraine | 
+| 26 | art - artist - work - painting - pinata | 25 | 26_art_artist_work_painting | 
+| 27 | economy - eurozone - european - euro - debt | 24 | 27_economy_eurozone_european_euro | 
+| 28 | north - kim - korea - korean - jong | 24 | 28_north_kim_korea_korean | 
+| 29 | ebola - virus - liberia - africa - outbreak | 22 | 29_ebola_virus_liberia_africa | 
+| 30 | bike - speed - road - driver - cyclist | 22 | 30_bike_speed_road_driver | 
+| 31 | car - accident - driver - scene - crash | 20 | 31_car_accident_driver_scene | 
+| 32 | price - london - house - home - property | 20 | 32_price_london_house_home | 
+| 33 | al - qaeda - yemen - us - yemeni | 20 | 33_al_qaeda_yemen_us | 
+| 34 | mrs - police - murder - greaves - mr | 20 | 34_mrs_police_murder_greaves | 
+| 35 | per - cent - people - age - average | 19 | 35_per_cent_people_age | 
+| 36 | philpott - court - berry - husband - dewani | 18 | 36_philpott_court_berry_husband | 
+| 37 | facebook - photo - user - instagram - cuddle | 17 | 37_facebook_photo_user_instagram | 
+| 38 | vaccine - meningitis - disease - flu - princeton | 17 | 38_vaccine_meningitis_disease_flu | 
+| 39 | bear - lion - gorilla - cub - zoo | 16 | 39_bear_lion_gorilla_cub | 
+| 40 | brain - drug - alzheimers - memory - patient | 16 | 40_brain_drug_alzheimers_memory | 
+| 41 | prince - royal - queen - duchess - duke | 16 | 41_prince_royal_queen_duchess | 
+| 42 | boat - ship - river - vessel - ferry | 15 | 42_boat_ship_river_vessel | 
+| 43 | china - chinese - chinas - organ - hong | 14 | 43_china_chinese_chinas_organ | 
+| 44 | egypt - election - egyptian - mubarak - protest | 13 | 44_egypt_election_egyptian_mubarak | 
+| 45 | mexico - mexican - cartel - mexicos - drug | 13 | 45_mexico_mexican_cartel_mexicos | 
+| 46 | cia - assange - snowden - us - interrogation | 13 | 46_cia_assange_snowden_us | 
+| 47 | police - hartman - hore - store - maitua | 13 | 47_police_hartman_hore_store | 
+| 48 | israeli - israel - palestinian - gaza - hamas | 12 | 48_israeli_israel_palestinian_gaza | 
+| 49 | pension - tax - scheme - energy - cent | 12 | 49_pension_tax_scheme_energy | 
+| 50 | council - neighbour - village - site - shed | 12 | 50_council_neighbour_village_site | 
+| 51 | occupy - protester - york - cosby - mayor | 11 | 51_occupy_protester_york_cosby | 
+| 52 | mould - allergic - allergy - reaction - hand | 11 | 52_mould_allergic_allergy_reaction | 
+| 53 | boko - haram - nigeria - sudan - isis | 11 | 53_boko_haram_nigeria_sudan | 
+| 54 | disaster - building - tsunami - people - quake | 11 | 54_disaster_building_tsunami_people | 
+| 55 | castro - sloot - der - ariel - aruba | 11 | 55_castro_sloot_der_ariel |
+  
+</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: False
+
+## Framework versions
+
+* Numpy: 1.22.4
+* HDBSCAN: 0.8.33
+* UMAP: 0.5.3
+* Pandas: 1.5.3
+* Scikit-Learn: 1.2.2
+* Sentence-transformers: 2.2.2
+* Transformers: 4.31.0
+* Numba: 0.56.4
+* Plotly: 5.13.1
+* Python: 3.10.6

config.json

@@ -0,0 +1,15 @@
+{
+  "calculate_probabilities": true,
+  "language": "english",
+  "low_memory": false,
+  "min_topic_size": 10,
+  "n_gram_range": [
+    1,
+    1
+  ],
+  "nr_topics": null,
+  "seed_topic_list": null,
+  "top_n_words": 10,
+  "verbose": false,
+  "embedding_model": "sentence-transformers/all-MiniLM-L6-v2"
+}

topic_embeddings.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d78dab072cc6245855f02276dd8f26679c79177364139a94bd4ad0a2d790d9ec
+size 87640

topics.json

@@ -0,0 +1,5808 @@
+{
+  "topic_representations": {
+    "-1": [
+      [
+        "said",
+        0.010915431333731507
+      ],
+      [
+        "one",
+        0.006937421358460086
+      ],
+      [
+        "police",
+        0.006708694698848247
+      ],
+      [
+        "people",
+        0.0067037879747290086
+      ],
+      [
+        "year",
+        0.006445173710037594
+      ],
+      [
+        "also",
+        0.005894131271515249
+      ],
+      [
+        "would",
+        0.005856593637765168
+      ],
+      [
+        "time",
+        0.005789448089091323
+      ],
+      [
+        "two",
+        0.005563617758218557
+      ],
+      [
+        "new",
+        0.0054697226062508505
+      ]
+    ],
+    "0": [
+      [
+        "league",
+        0.020033230852045746
+      ],
+      [
+        "player",
+        0.018335927996558764
+      ],
+      [
+        "cup",
+        0.01575108925388018
+      ],
+      [
+        "goal",
+        0.01521307048571138
+      ],
+      [
+        "game",
+        0.014791842299203052
+      ],
+      [
+        "season",
+        0.01432145803049712
+      ],
+      [
+        "team",
+        0.012681544038612949
+      ],
+      [
+        "club",
+        0.012611826688993874
+      ],
+      [
+        "manchester",
+        0.01259130841787106
+      ],
+      [
+        "united",
+        0.012149324856896045
+      ]
+    ],
+    "1": [
+      [
+        "police",
+        0.020828216445224385
+      ],
+      [
+        "said",
+        0.016287463781145983
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+      [
+        "home",
+        0.012913639567381743
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+      [
+        "murder",
+        0.012541432431031991
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+      [
+        "found",
+        0.012420705703530729
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+      [
+        "told",
+        0.01192309208441737
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+      [
+        "shot",
+        0.011213718941523317
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+      [
+        "court",
+        0.010202028479128433
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+      [
+        "death",
+        0.009908331235712498
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+      [
+        "shooting",
+        0.009881872374560287
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+    "2": [
+      [
+        "court",
+        0.016271285071156553
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+      [
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+        0.013244461755119594
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+      [
+        "said",
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+      [
+        "year",
+        0.01070263727298662
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+      [
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+        0.010548572141688393
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+      [
+        "child",
+        0.010504107796467212
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+      [
+        "judge",
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+      [
+        "police",
+        0.009586076134025052
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+      [
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+        0.009577994917384045
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+      [
+        "abuse",
+        0.009169260195293127
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+    ],
+    "3": [
+      [
+        "obama",
+        0.029523097793300042
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+      [
+        "president",
+        0.020246812243740003
+      ],
+      [
+        "republicans",
+        0.016468732570086842
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+      [
+        "house",
+        0.013611150825180732
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+      [
+        "republican",
+        0.013363532456159146
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+      [
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+        0.012074033761745791
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+      [
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+      [
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+      [
+        "said",
+        0.011073933455166494
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+      [
+        "obamas",
+        0.010420266900407829
+      ]
+    ],
+    "4": [
+      [
+        "plane",
+        0.05040997605496398
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+      [
+        "flight",
+        0.049666393886073294
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+      [
+        "passenger",
+        0.02562074022360435
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+      [
+        "airport",
+        0.02394637460455735
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+      [
+        "aircraft",
+        0.023578629691745397
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+      [
+        "air",
+        0.021593829335053737
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+      [
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+        0.017537117039435474
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+      [
+        "said",
+        0.017273360644784182
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+      [
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+        0.015721948803879754
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+      [
+        "landing",
+        0.014585023506066977
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+    "5": [
+      [
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+        0.021053947371478816
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+      [
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+        0.013773366977617272
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+      [
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+        0.012987271915225758
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+      [
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+        0.012510145219909773
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+      [
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+      [
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+    "7": [
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+      [
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+        0.04210832742992434
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+      [
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+        0.03465877473898644
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+      [
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+      [
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+      [
+        "college",
+        0.012151632224580308
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+    "13": [
+      [
+        "murray",
+        0.04003664155332171
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+      [
+        "wimbledon",
+        0.028852785944622657
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+      [
+        "win",
+        0.023082111950107995
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+      [
+        "champion",
+        0.02226657380383668
+      ],
+      [
+        "match",
+        0.020430585948502486
+      ],
+      [
+        "federer",
+        0.02032965988869585
+      ],
+      [
+        "round",
+        0.018015954354125674
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+      [
+        "title",
+        0.01797534093883942
+      ],
+      [
+        "djokovic",
+        0.015873375594543864
+      ],
+      [
+        "troicki",
+        0.015352272150315954
+      ]
+    ],
+    "14": [
+      [
+        "race",
+        0.023618462526068123
+      ],
+      [
+        "prix",
+        0.021562468259396908
+      ],
+      [
+        "hamilton",
+        0.021153552866326985
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+      [
+        "gold",
+        0.01967079939213285
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+      [
+        "world",
+        0.01939451318401775
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+      [
+        "champion",
+        0.01850993774624562
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+      [
+        "schumacher",
+        0.017072934307608766
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+      [
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+        0.016254414590275698
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+      [
+        "team",
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+    "15": [
+      [
+        "dog",
+        0.09488987498787448
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+      [
+        "animal",
+        0.04260168341416294
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+      [
+        "owner",
+        0.02606862146866785
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+      [
+        "dogs",
+        0.01803296066480757
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+      [
+        "tiger",
+        0.01663333080596362
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+      [
+        "puppy",
+        0.015359493002854524
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+      [
+        "park",
+        0.014193260354437014
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+      [
+        "pet",
+        0.013974942379764276
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+      [
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