label_model_merged

davanstrien/label_model_merged

label_model_merged is a text classification model from davanstrien. Use it when you need a label for a piece of text. It is set up for bertopic.

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.

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At a glance

Task: Text Classification
Library: bertopic
Access: Public
Created: Jun 6, 2023
Updated: Jun 6, 2023
SHA: 4dd3b940

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Model card

From the Hugging Face model README

label_model_merged

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("davanstrien/label_model_merged")

topic_model.get_topic_info()

Topic overview

Number of topics: 247
Number of training documents: 14986

<details> <summary>Click here for an overview of all topics.</summary>

Topic ID	Topic Keywords	Topic Frequency	Label
-1	pre - roll - heavy - farm - health	5	-1_pre_roll_heavy_farm
0	label_1 label_2 - label_0 label_1 label_2 - label_1 - label_0 label_1 - label_2	1386	0_label_1 label_2_label_0 label_1 label_2_label_1_label_0 label_1
1	label_1 label_2 label_3 - label_3 label_4 label_5 - label_4 label_5 - label_2 label_3 label_4 - label_5	1042	1_label_1 label_2 label_3_label_3 label_4 label_5_label_4 label_5_label_2 label_3 label_4
2	negative positive - positive negative - negative - positive - target	803	2_negative positive_positive negative_negative_positive
3	loc misc org - misc org - loc misc - misc - org loc	652	3_loc misc org_misc org_loc misc_misc
4	neutral positive - neutral - positive negative - negative - positive	509	4_neutral positive_neutral_positive negative_negative
5	label_0 - country - city - label_1 - label_0 label_1	357	5_label_0_country_city_label_1
6	contradiction - entailment - neutral - -	351	6_contradiction_entailment_neutral_
7	label_0 - positive - - -	335	7_label_0_positive__
8	99 - - - -	327	8_99___
9	label_1 label_2 label_3 - label_2 label_3 label_4 - label_3 label_4 - label_2 label_3 - label_4	302	9_label_1 label_2 label_3_label_2 label_3 label_4_label_3 label_4_label_2 label_3
10	entailment - true - child - related - non	257	10_entailment_true_child_related
11	terrier - snake - dog - bear - wolf	245	11_terrier_snake_dog_bear
12	loc misc org - loc misc - misc org - misc - org loc	240	12_loc misc org_loc misc_misc org_misc
13	label_5 label_6 label_7 - label_6 label_7 - label_4 label_5 label_6 - label_5 label_6 - label_7	231	13_label_5 label_6 label_7_label_6 label_7_label_4 label_5 label_6_label_5 label_6
14	calendar - greeting - weather - transfer - calculator	229	14_calendar_greeting_weather_transfer
15	label_1 label_2 label_3 - label_2 label_3 - label_3 - label_1 label_2 - label_0 label_1 label_2	226	15_label_1 label_2 label_3_label_2 label_3_label_3_label_1 label_2
16	delete - unrelated - bad - related - rel	207	16_delete_unrelated_bad_related
17	label_12 label_13 label_14 - label_11 label_12 label_13 - label_13 label_14 - label_12 label_13 - label_10 label_11 label_12	172	17_label_12 label_13 label_14_label_11 label_12 label_13_label_13 label_14_label_12 label_13
18	loc org - org loc - org - loc - loc loc	166	18_loc org_org loc_org_loc
19	left - right - stop - yes - zero	130	19_left_right_stop_yes
20	label_6 label_60 label_61 - label_60 label_61 - label_60 label_61 label_62 - label_62 label_63 - label_59 label_6 label_60	123	20_label_6 label_60 label_61_label_60 label_61_label_60 label_61 label_62_label_62 label_63
21	unrelated - - - -	117	21_unrelated___
22	forest - industrial - river - transport - disaster	110	22_forest_industrial_river_transport
23	label_4 label_5 label_6 - label_5 label_6 - label_6 - label_1 label_2 label_3 - label_3 label_4 label_5	107	23_label_4 label_5 label_6_label_5 label_6_label_6_label_1 label_2 label_3
24	question - quantity - - -	106	24_question_quantity__
25	healthy - leaf - rust - plant - mildew	103	25_healthy_leaf_rust_plant
26	disease - blood - bio - healthy - sexual	100	26_disease_blood_bio_healthy
27	work - group - corporation - person product - product	92	27_work_group_corporation_person product
28	surprise anger - sadness surprise - fear joy - anger fear - joy love	80	28_surprise anger_sadness surprise_fear joy_anger fear
29	duplicate - common - non - -	78	29_duplicate_common_non_
30	steak - hamburger - restaurant - pizza - joint	76	30_steak_hamburger_restaurant_pizza
31	room - service - transport - product - forest	74	31_room_service_transport_product
32	dis - - - -	74	32_dis___
33	- - - -	73	33____
34	loc org - org - date - loc - set	70	34_loc org_org_date_loc
35	label_17 label_18 label_19 - label_18 label_19 - label_18 label_19 label_2 - label_19 label_2 - label_16 label_17 label_18	70	35_label_17 label_18 label_19_label_18 label_19_label_18 label_19 label_2_label_19 label_2
36	03 - 02 - second - -	65	36_03_02_second_
37	anger fear - joy love - surprise - joy - love	65	37_anger fear_joy love_surprise_joy
38	real - true - image - news -	64	38_real_true_image_news
39	- - - -	63	39____
40	pos - neg - neu - -	62	40_pos_neg_neu_
41	45 - 30 - 55 - 35 - 10	61	41_45_30_55_35
42	ge - wifi - na - alpha - fan	61	42_ge_wifi_na_alpha
43	label_1 label_10 label_11 - label_10 label_11 - label_8 label_9 label_0 - label_9 label_0 label_1 - label_9 label_0	61	43_label_1 label_10 label_11_label_10 label_11_label_8 label_9 label_0_label_9 label_0 label_1
44	event - group - corporation - person product - product	61	44_event_group_corporation_person product
45	label_19 label_2 label_20 - label_2 label_20 - label_20 - label_18 label_19 label_2 - label_18 label_19	60	45_label_19 label_2 label_20_label_2 label_20_label_20_label_18 label_19 label_2
46	fear happy - sad - happy - disgust fear - angry	58	46_fear happy_sad_happy_disgust fear
47	battery - volume - chinese - juice - socks	58	47_battery_volume_chinese_juice
48	prep - nn - bio - cc - pro	56	48_prep_nn_bio_cc
49	good - poor - ok - great - bad	56	49_good_poor_ok_great
50	date - city - fur - day - ar	54	50_date_city_fur_day
51	15 - 18 19 20 - 19 20 - 17 18 19 - 18 19	54	51_15_18 19 20_19 20_17 18 19
52	menu - price - num - -	52	52_menu_price_num_
53	common - fat - loose - small - sugar	52	53_common_fat_loose_small
54	append_ - replace_ - append_ append_ - replace_ replace_ - append_ append_ append_	49	54_append__replace__append_ append__replace_ replace_
55	append_ - replace_ - append_ append_ - replace_ replace_ - append_ append_ append_	48	55_append__replace__append_ append__replace_ replace_
56	animals - flying - tech - dance - tiger	48	56_animals_flying_tech_dance
57	self - question - neutral - yes - greeting	47	57_self_question_neutral_yes
58	mt - cv - tr - tm - drug	47	58_mt_cv_tr_tm
59	organization person - location organization - organization - location - person	46	59_organization person_location organization_organization_location
60	- - - -	45	60____
61	joy - anger - sadness - sad - happy	44	61_joy_anger_sadness_sad
62	daisy - tulip - rose - -	43	62_daisy_tulip_rose_
63	positive - negative - neutral - neutral positive - positive negative	42	63_positive_negative_neutral_neutral positive
64	windows - pm - 21 - office - 20	42	64_windows_pm_21_office
65	label_14 label_15 - label_13 label_14 label_15 - label_15 - label_12 label_13 label_14 - label_11 label_12 label_13	42	65_label_14 label_15_label_13 label_14 label_15_label_15_label_12 label_13 label_14
66	position - statement - lead - request - study	42	66_position_statement_lead_request
67	business - news - entertainment - tech - sport	41	67_business_news_entertainment_tech
68	hate - speech - language - reporting - non	41	68_hate_speech_language_reporting
69	bd - nan - id - bg -	41	69_bd_nan_id_bg
70	cream - burger - carrot - ice cream - salad	41	70_cream_burger_carrot_ice cream
71	human - machine - ai - artificial - art	40	71_human_machine_ai_artificial
72	open - high - tie - abstract - button	40	72_open_high_tie_abstract
73	label_23 label_24 label_25 - label_24 label_25 - label_22 label_23 label_24 - label_23 label_24 - label_21 label_22 label_23	40	73_label_23 label_24 label_25_label_24 label_25_label_22 label_23 label_24_label_23 label_24
74	label_8 label_9 label_0 - label_9 label_0 label_1 - label_9 label_0 - label_7 label_8 label_9 - label_8 label_9	39	74_label_8 label_9 label_0_label_9 label_0 label_1_label_9 label_0_label_7 label_8 label_9
75	cat - dog - cats - dogs - drinking	39	75_cat_dog_cats_dogs
76	org org - loc loc - org - misc - loc	38	76_org org_loc loc_org_misc
77	airplane - deer - bird - ship - frog	38	77_airplane_deer_bird_ship
78	label_32 label_33 label_34 - label_33 label_34 - label_31 label_32 label_33 - label_32 label_33 - label_30 label_31 label_32	38	78_label_32 label_33 label_34_label_33 label_34_label_31 label_32 label_33_label_32 label_33
79	true - - - -	38	79_true___
80	family - sports - music - related - health	38	80_family_sports_music_related
81	star - positive - negative - amazon - negative positive	37	81_star_positive_negative_amazon
82	hospital - unknown - description - material - pad	37	82_hospital_unknown_description_material
83	threat - hate - reward - quality - content	36	83_threat_hate_reward_quality
84	music - speech - instrument - engine - wind	35	84_music_speech_instrument_engine
85	closure - annual - statement - issues - reward	35	85_closure_annual_statement_issues
86	adp - aux - sconj - pron - noun	35	86_adp_aux_sconj_pron
87	experience - location - skill - address - result	35	87_experience_location_skill_address
88	- - - -	34	88____
89	test - train - risk - non - high	34	89_test_train_risk_non
90	samoyed - corgi - husky - golden retriever - golden	34	90_samoyed_corgi_husky_golden retriever
91	unk - zero - 10 - 12 13 14 - 13 14 15	33	91_unk_zero_10_12 13 14
92	non - neutral - ok - lead -	33	92_non_neutral_ok_lead
93	normal - covid - virus - regular - disorder	33	93_normal_covid_virus_regular
94	test - help - app - risk - joke	32	94_test_help_app_risk
95	replace_ - append_ - replace_ replace_ - append_ append_ - replace_ replace_ replace_	32	95_replace__append__replace_ replace__append_ append_
96	disease - issues - pressure - drug - blood	31	96_disease_issues_pressure_drug
97	women - casual - sexual - individual - use	31	97_women_casual_sexual_individual
98	address - balance - code - second - currency	30	98_address_balance_code_second
99	hate - non - neutral - -	30	99_hate_non_neutral_
100	normal - cell - large - clean - healthy	29	100_normal_cell_large_clean
101	neutral - se - - -	29	101_neutral_se__
102	male - female - hair - skin - men	29	102_male_female_hair_skin
103	title - page - section - abstract - table	28	103_title_page_section_abstract
104	number - gender - case - person - fin	28	104_number_gender_case_person
105	man - bird - flower - long - double	28	105_man_bird_flower_long
106	contradiction - entailment - neutral - -	28	106_contradiction_entailment_neutral_
107	non - - - -	27	107_non___
108	tim - fac - org - pro - loc	27	108_tim_fac_org_pro
109	lincoln - jaguar - visual - audio - sony	27	109_lincoln_jaguar_visual_audio
110	statement - info - check - ad - news	27	110_statement_info_check_ad
111	ben - ext - root - exp - loc	26	111_ben_ext_root_exp
112	yes - - - -	26	112_yes___
113	queen - jack - king - south - war	26	113_queen_jack_king_south
114	- - - -	26	114____
115	ft - cardinal - act - loc - loc loc	25	115_ft_cardinal_act_loc
116	bio - chemical - food - -	25	116_bio_chemical_food_
117	ft - cardinal - act - loc - loc misc org	25	117_ft_cardinal_act_loc
118	metric - task - - -	25	118_metric_task__
119	email - age - patient - zip - organization	25	119_email_age_patient_zip
120	ent - im - ru - mat - art	25	120_ent_im_ru_mat
121	ex - pt - galaxy - moon - 8888	24	121_ex_pt_galaxy_moon
122	- - - -	24	122____
123	neu - sad - dis - joy -	24	123_neu_sad_dis_joy
124	label_122 - label_121 - label_120 - label_123 - label_119	24	124_label_122_label_121_label_120_label_123
125	mixed - positive - negative - neutral positive - neutral	24	125_mixed_positive_negative_neutral positive
126	date event - percent person - quantity - money - percent	24	126_date event_percent person_quantity_money
127	fear joy - sadness surprise - surprise - joy - sadness	24	127_fear joy_sadness surprise_surprise_joy
128	disgust - sadness surprise - joy love - surprise - joy	24	128_disgust_sadness surprise_joy love_surprise
129	magnet - motor - hello - undefined - start	24	129_magnet_motor_hello_undefined
130	loc loc - loc - pers - hi - en	24	130_loc loc_loc_pers_hi
131	event - pers - fac - pro - loc org	24	131_event_pers_fac_pro
132	disorder - body - patient - age - disease	23	132_disorder_body_patient_age
133	happiness - fear - anger disgust - disgust - sadness	23	133_happiness_fear_anger disgust_disgust
134	control - la - social - sin - civil	23	134_control_la_social_sin
135	label_98 label_99 - label_97 label_98 label_99 - label_97 label_98 - label_95 label_96 - label_96 label_97 label_98	23	135_label_98 label_99_label_97 label_98 label_99_label_97 label_98_label_95 label_96
136	greek - chinese - italian - japanese - dutch	23	136_greek_chinese_italian_japanese
137	clean - - - -	23	137_clean___
138	protein - chemical - cell - -	22	138_protein_chemical_cell_
139	treatment - disease - location organization - organization person - organization	22	139_treatment_disease_location organization_organization person
140	institution - tools - org - loc - organization	22	140_institution_tools_org_loc
141	statement - question - - -	22	141_statement_question__
142	period - question - noun - number -	21	142_period_question_noun_number
143	regular - - - -	21	143_regular___
144	rna - - - -	21	144_rna___
145	rs - - - -	21	145_rs___
146	address - id - job - email - country	21	146_address_id_job_email
147	neg - neu - good - -	21	147_neg_neu_good_
148	label_122 label_123 - label_123 - label_122 - label_121 - label_120	20	148_label_122 label_123_label_123_label_122_label_121
149	drink - tea - wine - coffee - soft	20	149_drink_tea_wine_coffee
150	miscellaneous - organization - percent - money - percent person	20	150_miscellaneous_organization_percent_money
151	description - invoice - zip - state - city	20	151_description_invoice_zip_state
152	sports - tech - business - sport -	20	152_sports_tech_business_sport
153	ok - vin - rl - ft - year	20	153_ok_vin_rl_ft
154	healthy - - - -	20	154_healthy___
155	association - event - ticket - disaster - map	20	155_association_event_ticket_disaster
156	10 11 - 10 11 12 - 11 12 - 11 - 11 12 13	19	156_10 11_10 11 12_11 12_11
157	noun num pron - num pron propn - num pron - pron propn punct - pron propn	19	157_noun num pron_num pron propn_num pron_pron propn punct
158	cell - organ - organism - multi - tissue	18	158_cell_organ_organism_multi
159	02 - ent - express - act - delete	18	159_02_ent_express_act
160	sym verb adj - verb adj adp - intj noun num - det intj noun - adj adp adv	18	160_sym verb adj_verb adj adp_intj noun num_det intj noun
161	12 - - - -	18	161_12___
162	org org - org - drug - -	18	162_org org_org_drug_
163	short - long - sl - ac - pad	18	163_short_long_sl_ac
164	plastic - paper - glass - metal - sheet	18	164_plastic_paper_glass_metal
165	ii - blank - iii - vi - et	17	165_ii_blank_iii_vi
166	normal - virus - desert - smoke - pressure	17	166_normal_virus_desert_smoke
167	skill - skills - - -	17	167_skill_skills__
168	protein - rna - cell - line - type	17	168_protein_rna_cell_line
169	korean - russian - dutch - french - thai	17	169_korean_russian_dutch_french
170	rainbow - rain - snow - color - green	17	170_rainbow_rain_snow_color
171	company - role - institution - skill - loc org	16	171_company_role_institution_skill
172	exp - pp - intj - punc - prep	16	172_exp_pp_intj_punc
173	key - menu - - -	16	173_key_menu__
174	adult - young - child - male - female	16	174_adult_young_child_male
175	normal - - - -	16	175_normal___
176	mask - bright - sharp - head - normal	16	176_mask_bright_sharp_head
177	anger disgust fear - anger disgust - disgust fear - disgust - surprise anger	16	177_anger disgust fear_anger disgust_disgust fear_disgust
178	- - - -	16	178____
179	objective - non - neutral - -	16	179_objective_non_neutral_
180	cr - sd - db - -	16	180_cr_sd_db_
181	- - - -	16	181____
182	label_29 label_3 label_30 - label_27 label_28 label_29 - label_26 label_27 label_28 - label_28 label_29 label_3 - label_29 label_3	16	182_label_29 label_3 label_30_label_27 label_28 label_29_label_26 label_27 label_28_label_28 label_29 label_3
183	test - - - -	15	183_test___
184	good - bad - non - -	15	184_good_bad_non_
185	local - por - art - da - em	15	185_local_por_art_da
186	label_122 label_123 - label_97 label_98 label_99 - label_97 label_98 - label_96 label_97 label_98 - label_98 label_99	15	186_label_122 label_123_label_97 label_98 label_99_label_97 label_98_label_96 label_97 label_98
187	prod - loc - evt - misc - org org	15	187_prod_loc_evt_misc
188	invoice - email - form - letter - report	15	188_invoice_email_form_letter
189	end - head - cross - -	15	189_end_head_cross_
190	target - instrument - opinion - question - price	15	190_target_instrument_opinion_question
191	unrelated - support - - -	15	191_unrelated_support__
192	ru - pl - bg - en - es	14	192_ru_pl_bg_en
193	road - good - bike - -	14	193_road_good_bike_
194	human - organism - plants - -	14	194_human_organism_plants_
195	label_7 label_8 label_9 - label_8 label_9 - label_0 label_1 label_10 - label_1 label_10 - label_10	14	195_label_7 label_8 label_9_label_8 label_9_label_0 label_1 label_10_label_1 label_10
196	replace_ - append_ - replace_ replace_ - append_ append_ - replace_ replace_ replace_	13	196_replace__append__replace_ replace__append_ append_
197	brand - company - tm - color - item	13	197_brand_company_tm_color
198	pro - neutral - russian - support - attack	13	198_pro_neutral_russian_support
199	18 19 20 - 19 20 - 23 - 17 18 19 - 21	13	199_18 19 20_19 20_23_17 18 19
200	crime - pers - time - book - day	13	200_crime_pers_time_book
201	neutral - positive - negative - positive negative - neutral positive	13	201_neutral_positive_negative_positive negative
202	- - - -	13	202____
203	chemical - disease - bio - -	13	203_chemical_disease_bio_
204	angry - happy - sad - neutral - 60	12	204_angry_happy_sad_neutral
205	organisation - task - country - location - product	12	205_organisation_task_country_location
206	iv - iii - vi - ii - unknown	12	206_iv_iii_vi_ii
207	neutral - risk - - -	12	207_neutral_risk__
208	container - id - type - person - number	12	208_container_id_type_person
209	target - - - -	12	209_target___
210	pop - metal - country - song - rock	12	210_pop_metal_country_song
211	email - os - language - method - function	12	211_email_os_language_method
212	contradiction - non - entailment - -	12	212_contradiction_non_entailment_
213	background - objective - method - result -	12	213_background_objective_method_result
214	convertible - cab - type - series - martin	12	214_convertible_cab_type_series
215	public - smoking - drinking - ambiguous - non	12	215_public_smoking_drinking_ambiguous
216	rust - - - -	12	216_rust___
217	persian - mr - man - flying - ghost	12	217_persian_mr_man_flying
218	quote - yes - middle - request -	12	218_quote_yes_middle_request
219	text - mixed - - -	12	219_text_mixed__
220	punc - prep - digit - latin - conj	12	220_punc_prep_digit_latin
221	panda - air - mr - ticket - little	12	221_panda_air_mr_ticket
222	- - - -	12	222____
223	sym verb adj - intj noun num - verb adj adp - cconj det intj - aux cconj det	12	223_sym verb adj_intj noun num_verb adj adp_cconj det intj
224	healthy - tomato - plant - pepper - spot	11	224_healthy_tomato_plant_pepper
225	sony - lg - tv - galaxy - monitor	11	225_sony_lg_tv_galaxy
226	new - city - mid - location - south	11	226_new_city_mid_location
227	space - - - -	11	227_space___
228	cloud - racing - motorcycle - boy - bus	11	228_cloud_racing_motorcycle_boy
229	punc - zero - pers - neg - reflex	11	229_punc_zero_pers_neg
230	energy - arts - high - systems - computer	11	230_energy_arts_high_systems
231	dis - ad - media - site - plant	11	231_dis_ad_media_site
232	world - tech - business - sports - female	11	232_world_tech_business_sports
233	sadness - anger - anger fear - joy - fear	10	233_sadness_anger_anger fear_joy
234	neg - adj - sym - propn - num	10	234_neg_adj_sym_propn
235	bulldog - cat - husky - pug - corgi	9	235_bulldog_cat_husky_pug
236	- - - -	8	236____
237	origin - quote - actor - opinion - language	7	237_origin_quote_actor_opinion
238	na - nb - nc - neu - ng	7	238_na_nb_nc_neu
239	- - - -	7	239____
240	ci - aa - joy - im - ip	7	240_ci_aa_joy_im
241	- - - -	6	241____
242	skill - email - address - grade - language	6	242_skill_email_address_grade
243	sexual - threat - christian - hate - male	6	243_sexual_threat_christian_hate
244	transmission - wind - tower - pole -	6	244_transmission_wind_tower_pole
245	label_14 label_15 - label_13 label_14 label_15 - label_15 - label_12 label_13 label_14 - label_11 label_12 label_13	6	245_label_14 label_15_label_13 label_14 label_15_label_15_label_12 label_13 label_14

</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: True

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: 4.29.2
Numba: 0.56.4
Plotly: 5.13.1
Python: 3.10.11

Task: Text Classification
Library: bertopic
Created: Jun 6, 2023
Updated: Jun 6, 2023