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KingKazma
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cnn_dailymail_108_3000_1500_test

Text Classification
BERTopic
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Files changed (4) hide show
  1. README.md +96 -0
  2. config.json +15 -0
  3. topic_embeddings.safetensors +3 -0
  4. topics.json +2936 -0
README.md ADDED
@@ -0,0 +1,96 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+ ---
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+ tags:
4
+ - bertopic
5
+ library_name: bertopic
6
+ pipeline_tag: text-classification
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+ ---
8
+
9
+ # cnn_dailymail_108_3000_1500_test
10
+
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+ This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model.
12
+ BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets.
13
+
14
+ ## Usage
15
+
16
+ To use this model, please install BERTopic:
17
+
18
+ ```
19
+ pip install -U bertopic
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+ ```
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+
22
+ You can use the model as follows:
23
+
24
+ ```python
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+ from bertopic import BERTopic
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+ topic_model = BERTopic.load("KingKazma/cnn_dailymail_108_3000_1500_test")
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+
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+ topic_model.get_topic_info()
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+ ```
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+
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+ ## Topic overview
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+
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+ * Number of topics: 29
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+ * Number of training documents: 1500
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+
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+ <details>
37
+ <summary>Click here for an overview of all topics.</summary>
38
+
39
+ | Topic ID | Topic Keywords | Topic Frequency | Label |
40
+ |----------|----------------|-----------------|-------|
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+ | -1 | said - one - year - time - people | 11 | -1_said_one_year_time |
42
+ | 0 | police - said - told - school - court | 384 | 0_police_said_told_school |
43
+ | 1 | game - liverpool - league - goal - season | 249 | 1_game_liverpool_league_goal |
44
+ | 2 | said - attack - group - police - people | 91 | 2_said_attack_group_police |
45
+ | 3 | people - said - planet - mountain - mile | 85 | 3_people_said_planet_mountain |
46
+ | 4 | baby - family - mother - said - cancer | 77 | 4_baby_family_mother_said |
47
+ | 5 | labour - mr - miliband - tax - leader | 54 | 5_labour_mr_miliband_tax |
48
+ | 6 | shark - crocodile - fish - animal - water | 49 | 6_shark_crocodile_fish_animal |
49
+ | 7 | chelsea - arsenal - mourinho - hazard - league | 37 | 7_chelsea_arsenal_mourinho_hazard |
50
+ | 8 | united - manchester - city - van - league | 36 | 8_united_manchester_city_van |
51
+ | 9 | masters - round - woods - group - tournament | 31 | 9_masters_round_woods_group |
52
+ | 10 | model - fashion - dress - woman - look | 30 | 10_model_fashion_dress_woman |
53
+ | 11 | food - sugar - restaurant - water - vitamin | 29 | 11_food_sugar_restaurant_water |
54
+ | 12 | race - hamilton - rosberg - grand - prix | 29 | 12_race_hamilton_rosberg_grand |
55
+ | 13 | madrid - ronaldo - real - goal - barcelona | 29 | 13_madrid_ronaldo_real_goal |
56
+ | 14 | england - cricket - test - cook - benaud | 28 | 14_england_cricket_test_cook |
57
+ | 15 | clinton - president - obama - hillary - said | 27 | 15_clinton_president_obama_hillary |
58
+ | 16 | property - house - home - market - apartment | 25 | 16_property_house_home_market |
59
+ | 17 | fight - mayweather - pacquiao - manny - bout | 25 | 17_fight_mayweather_pacquiao_manny |
60
+ | 18 | apple - watch - price - per - cent | 24 | 18_apple_watch_price_per |
61
+ | 19 | celtic - rangers - game - scottish - deila | 24 | 19_celtic_rangers_game_scottish |
62
+ | 20 | dog - animal - owner - council - dogs | 21 | 20_dog_animal_owner_council |
63
+ | 21 | prince - royal - harry - queen - baby | 21 | 21_prince_royal_harry_queen |
64
+ | 22 | film - actor - downey - interview - show | 17 | 22_film_actor_downey_interview |
65
+ | 23 | hotel - flight - mile - island - room | 16 | 23_hotel_flight_mile_island |
66
+ | 24 | bayern - guardiola - porto - dortmund - munich | 14 | 24_bayern_guardiola_porto_dortmund |
67
+ | 25 | wedding - gabriel - noah - roxy - sandra | 13 | 25_wedding_gabriel_noah_roxy |
68
+ | 26 | saracens - bosch - penalty - kick - rugby | 12 | 26_saracens_bosch_penalty_kick |
69
+ | 27 | deal - summer - club - interest - contract | 12 | 27_deal_summer_club_interest |
70
+
71
+ </details>
72
+
73
+ ## Training hyperparameters
74
+
75
+ * calculate_probabilities: True
76
+ * language: english
77
+ * low_memory: False
78
+ * min_topic_size: 10
79
+ * n_gram_range: (1, 1)
80
+ * nr_topics: None
81
+ * seed_topic_list: None
82
+ * top_n_words: 10
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+ * verbose: False
84
+
85
+ ## Framework versions
86
+
87
+ * Numpy: 1.22.4
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+ * HDBSCAN: 0.8.33
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+ * UMAP: 0.5.3
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+ * Pandas: 1.5.3
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+ * Scikit-Learn: 1.2.2
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+ * Sentence-transformers: 2.2.2
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+ * Transformers: 4.31.0
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+ * Numba: 0.56.4
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+ * Plotly: 5.13.1
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+ * Python: 3.10.6
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+ "embedding_model": "sentence-transformers/all-MiniLM-L6-v2"
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+ }
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