File size: 24,475 Bytes
3637239 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 |
---
tags:
- bertopic
library_name: bertopic
pipeline_tag: text-classification
---
# label_model
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("davanstrien/label_model")
topic_model.get_topic_info()
```
## Topic overview
* Number of topics: 252
* Number of training documents: 14986
<details>
<summary>Click here for an overview of all topics.</summary>
| Topic ID | Topic Keywords | Topic Frequency | Label |
|----------|----------------|-----------------|-------|
| -1 | date - city - pre - heavy - fur | 5 | -1_date_city_pre_heavy |
| 0 | label_1 label_2 - label_0 label_1 label_2 - label_0 label_1 - label_1 - label_2 | 1333 | 0_label_1 label_2_label_0 label_1 label_2_label_0 label_1_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 | 1043 | 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 - loc misc - misc org - misc - org loc | 651 | 3_loc misc org_loc misc_misc org_misc |
| 4 | neutral positive - neutral - positive negative - negative - positive | 479 | 4_neutral positive_neutral_positive negative_negative |
| 5 | label_0 - - - - | 357 | 5_label_0___ |
| 6 | contradiction - entailment - neutral - ambiguous - | 348 | 6_contradiction_entailment_neutral_ambiguous |
| 7 | label_0 - - - - | 334 | 7_label_0___ |
| 8 | 99 - - - - | 326 | 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 | 300 | 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 | snake - dog - bear - wolf - sea | 245 | 11_snake_dog_bear_wolf |
| 12 | label_5 label_6 label_7 - label_6 label_7 - label_4 label_5 label_6 - label_5 label_6 - label_6 label_7 label_8 | 241 | 12_label_5 label_6 label_7_label_6 label_7_label_4 label_5 label_6_label_5 label_6 |
| 13 | loc misc org - loc misc - misc org - misc - org loc | 229 | 13_loc misc org_loc misc_misc org_misc |
| 14 | weather - transfer - alarm - text - time | 228 | 14_weather_transfer_alarm_text |
| 15 | label_1 label_2 label_3 - label_2 label_3 - label_3 - label_1 label_2 - label_0 label_1 label_2 | 222 | 15_label_1 label_2 label_3_label_2 label_3_label_3_label_1 label_2 |
| 16 | delete - different - bad - related - rel | 207 | 16_delete_different_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 | - - - - | 166 | 18____ |
| 19 | loc org loc - loc org - org loc - org - loc | 142 | 19_loc org loc_loc org_org loc_org |
| 20 | label_6 label_60 label_61 - label_60 label_61 - label_62 label_63 - label_61 label_62 label_63 - label_61 label_62 | 126 | 20_label_6 label_60 label_61_label_60 label_61_label_62 label_63_label_61 label_62 label_63 |
| 21 | label_4 label_5 label_6 - label_5 label_6 - label_6 - label_1 label_2 label_3 - label_3 label_4 label_5 | 117 | 21_label_4 label_5 label_6_label_5 label_6_label_6_label_1 label_2 label_3 |
| 22 | test - second - - - | 106 | 22_test_second__ |
| 23 | forest - industrial - transport - low - bamboo | 104 | 23_forest_industrial_transport_low |
| 24 | answer - header - question - quantity - | 104 | 24_answer_header_question_quantity |
| 25 | healthy - leaf - rust - plant - spot | 103 | 25_healthy_leaf_rust_plant |
| 26 | left - right - stop - yes - unknown | 100 | 26_left_right_stop_yes |
| 27 | en - na - alpha - fan - lifestyle | 93 | 27_en_na_alpha_fan |
| 28 | label_13 label_14 label_15 - label_14 label_15 - label_15 - label_12 label_13 label_14 - label_11 label_12 label_13 | 92 | 28_label_13 label_14 label_15_label_14 label_15_label_15_label_12 label_13 label_14 |
| 29 | disease - bio - disorder - healthy - | 86 | 29_disease_bio_disorder_healthy |
| 30 | work - group - person product - product - location | 86 | 30_work_group_person product_product |
| 31 | fear joy - sadness surprise - anger fear - joy love - surprise | 82 | 31_fear joy_sadness surprise_anger fear_joy love |
| 32 | common - non - different - - | 78 | 32_common_non_different_ |
| 33 | dis - - - - | 76 | 33_dis___ |
| 34 | - - - - | 73 | 34____ |
| 35 | restaurant - pizza - place - salad - food | 69 | 35_restaurant_pizza_place_salad |
| 36 | cconj det intj - adj adp adv - det intj noun - det intj - noun num pron | 66 | 36_cconj det intj_adj adp adv_det intj noun_det intj |
| 37 | label_17 label_18 label_19 - label_18 label_19 label_2 - label_18 label_19 - label_19 label_2 - label_16 label_17 label_18 | 66 | 37_label_17 label_18 label_19_label_18 label_19 label_2_label_18 label_19_label_19 label_2 |
| 38 | ll - year - related - cause - delete | 65 | 38_ll_year_related_cause |
| 39 | anger fear - joy love - surprise - joy - love | 64 | 39_anger fear_joy love_surprise_joy |
| 40 | true - news - partial - - | 64 | 40_true_news_partial_ |
| 41 | - - - - | 63 | 41____ |
| 42 | label_1 label_10 label_11 - label_10 label_11 - label_8 label_9 label_0 - label_7 label_8 label_9 - label_8 label_9 | 62 | 42_label_1 label_10 label_11_label_10 label_11_label_8 label_9 label_0_label_7 label_8 label_9 |
| 43 | pos - neg - - - | 62 | 43_pos_neg__ |
| 44 | loc org - org - loc - date - sex | 61 | 44_loc org_org_loc_date |
| 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 | event - group - person product - product - location | 57 | 46_event_group_person product_product |
| 47 | bio - chemical - disease - effect - food | 57 | 47_bio_chemical_disease_effect |
| 48 | 234 - 19 20 21 - 20 21 22 - 22 23 24 - 23 24 | 57 | 48_234_19 20 21_20 21 22_22 23 24 |
| 49 | fear happy neutral - happy neutral - fear happy - sad - happy | 53 | 49_fear happy neutral_happy neutral_fear happy_sad |
| 50 | battery - volume - juice - chinese - korean | 53 | 50_battery_volume_juice_chinese |
| 51 | menu - price - num - - | 52 | 51_menu_price_num_ |
| 52 | poor - ok - good - bad - great | 52 | 52_poor_ok_good_bad |
| 53 | ll - cause - delete - unknown - | 51 | 53_ll_cause_delete_unknown |
| 54 | hospital - unknown - en - material - digital | 48 | 54_hospital_unknown_en_material |
| 55 | ll - cause - delete - unknown - | 48 | 55_ll_cause_delete_unknown |
| 56 | self - question - neutral - yes - statement | 48 | 56_self_question_neutral_yes |
| 57 | fat - loose - small - sugar - common | 47 | 57_fat_loose_small_sugar |
| 58 | true - - - - | 47 | 58_true___ |
| 59 | cream - drinks - seafood - fruit - ice cream | 46 | 59_cream_drinks_seafood_fruit |
| 60 | tr - ru - pers - pt - prod | 46 | 60_tr_ru_pers_pt |
| 61 | - - - - | 45 | 61____ |
| 62 | clothing - care - kitchen - personal - health | 44 | 62_clothing_care_kitchen_personal |
| 63 | business - news - tech - entertainment - sport | 43 | 63_business_news_tech_entertainment |
| 64 | non - partial - neutral - yes - ok | 43 | 64_non_partial_neutral_yes |
| 65 | organization person - location organization - organization - location - person | 43 | 65_organization person_location organization_organization_location |
| 66 | daisy - tulip - rose - - | 43 | 66_daisy_tulip_rose_ |
| 67 | joy - sadness - anger - angry - happy | 42 | 67_joy_sadness_anger_angry |
| 68 | samoyed - corgi - husky - pomeranian - golden | 41 | 68_samoyed_corgi_husky_pomeranian |
| 69 | music - instrument - engine - wind - animals | 41 | 69_music_instrument_engine_wind |
| 70 | hate - language - reporting - non - normal | 41 | 70_hate_language_reporting_non |
| 71 | 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 | 41 | 71_label_23 label_24 label_25_label_24 label_25_label_22 label_23 label_24_label_23 label_24 |
| 72 | id - - - - | 40 | 72_id___ |
| 73 | animals - tech - dance - tiger - sport | 40 | 73_animals_tech_dance_tiger |
| 74 | org org - loc loc - org - misc - loc | 40 | 74_org org_loc loc_org_misc |
| 75 | star - positive - negative - negative positive - | 38 | 75_star_positive_negative_negative positive |
| 76 | bird - ship - frog - horse - truck | 37 | 76_bird_ship_frog_horse |
| 77 | cat - cats - dog - dogs - sleeping | 37 | 77_cat_cats_dog_dogs |
| 78 | family - sports - music - related - health | 37 | 78_family_sports_music_related |
| 79 | 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 | 37 | 79_label_8 label_9 label_0_label_9 label_0 label_1_label_9 label_0_label_7 label_8 label_9 |
| 80 | room - service - transport - care - kitchen | 37 | 80_room_service_transport_care |
| 81 | positive - negative - neutral positive - neutral - positive negative | 37 | 81_positive_negative_neutral positive_neutral |
| 82 | test - play - train - non - live | 36 | 82_test_play_train_non |
| 83 | tim - evt - pro - gpe - org | 36 | 83_tim_evt_pro_gpe |
| 84 | cold - disease - pressure - drug - blood | 36 | 84_cold_disease_pressure_drug |
| 85 | non - early - late - - | 35 | 85_non_early_late_ |
| 86 | 21 - office - 20 - 17 - 16 | 34 | 86_21_office_20_17 |
| 87 | prep - nn - cc - pro - ex | 34 | 87_prep_nn_cc_pro |
| 88 | evidence - position - statement - lead - request | 33 | 88_evidence_position_statement_lead |
| 89 | adp - aux - sconj - cconj - det noun | 33 | 89_adp_aux_sconj_cconj |
| 90 | job - start - help - address - quantity | 33 | 90_job_start_help_address |
| 91 | gender - number - case - ind - person | 33 | 91_gender_number_case_ind |
| 92 | threat - hate - adult - target - male | 33 | 92_threat_hate_adult_target |
| 93 | institution - tools - organization - org - agent | 32 | 93_institution_tools_organization_org |
| 94 | - - - - | 32 | 94____ |
| 95 | email - age - patient - state - zip | 32 | 95_email_age_patient_state |
| 96 | mixed - positive - negative - neutral - neutral positive | 32 | 96_mixed_positive_negative_neutral |
| 97 | test - help - joke - contact - report | 32 | 97_test_help_joke_contact |
| 98 | address - balance - statement - request - second | 31 | 98_address_balance_statement_request |
| 99 | - - - - | 31 | 99____ |
| 100 | hate - non - neutral - - | 30 | 100_hate_non_neutral_ |
| 101 | - - - - | 30 | 101____ |
| 102 | unk - zero - seven - 10 - blank | 30 | 102_unk_zero_seven_10 |
| 103 | male - female - young - adult - skin | 30 | 103_male_female_young_adult |
| 104 | 94 - 59 60 - 49 50 - 81 - 97 | 29 | 104_94_59 60_49 50_81 |
| 105 | normal - cell - large - clean - lower | 29 | 105_normal_cell_large_clean |
| 106 | lincoln - jaguar - audio - source - general | 28 | 106_lincoln_jaguar_audio_source |
| 107 | title - section - header - list - item | 28 | 107_title_section_header_list |
| 108 | - - - - | 28 | 108____ |
| 109 | yes - - - - | 27 | 109_yes___ |
| 110 | - - - - | 26 | 110____ |
| 111 | contradiction - entailment - neutral - non - | 26 | 111_contradiction_entailment_neutral_non |
| 112 | instrument - org org - org org org - term - org | 26 | 112_instrument_org org_org org org_term |
| 113 | ft - cardinal - act - loc - loc loc | 25 | 113_ft_cardinal_act_loc |
| 114 | event - pro - pers - loc org - prod | 25 | 114_event_pro_pers_loc org |
| 115 | ben - ext - exp - root - loc | 25 | 115_ben_ext_exp_root |
| 116 | - - - - | 25 | 116____ |
| 117 | low - - - - | 25 | 117_low___ |
| 118 | ft - cardinal - act - loc - loc misc org | 25 | 118_ft_cardinal_act_loc |
| 119 | statement - question - evidence - experience - answer | 25 | 119_statement_question_evidence_experience |
| 120 | label_122 - label_121 - label_120 - label_123 - label_119 | 24 | 120_label_122_label_121_label_120_label_123 |
| 121 | clean - - - - | 24 | 121_clean___ |
| 122 | ru - tr - el - en - hi | 24 | 122_ru_tr_el_en |
| 123 | disgust - sadness surprise - joy love - surprise - joy | 24 | 123_disgust_sadness surprise_joy love_surprise |
| 124 | statement - info - check - news - non | 24 | 124_statement_info_check_news |
| 125 | motor - start - help - housing - yes | 24 | 125_motor_start_help_housing |
| 126 | greek - chinese - italian - japanese - dutch | 24 | 126_greek_chinese_italian_japanese |
| 127 | anger disgust - fear - disgust - sadness - anger | 23 | 127_anger disgust_fear_disgust_sadness |
| 128 | date event - percent person - quantity - money - percent | 23 | 128_date event_percent person_quantity_money |
| 129 | label_95 label_96 label_97 - label_97 label_98 label_99 - label_97 label_98 - label_94 label_95 label_96 - label_94 label_95 | 23 | 129_label_95 label_96 label_97_label_97 label_98 label_99_label_97 label_98_label_94 label_95 label_96 |
| 130 | period - question - noun - number - | 23 | 130_period_question_noun_number |
| 131 | neutral - - - - | 22 | 131_neutral___ |
| 132 | local - la - pad - data - personal | 22 | 132_local_la_pad_data |
| 133 | partial - - - - | 22 | 133_partial___ |
| 134 | human - art - machine - - | 22 | 134_human_art_machine_ |
| 135 | fear joy - sadness surprise - surprise - disgust fear - joy | 21 | 135_fear joy_sadness surprise_surprise_disgust fear |
| 136 | location organization - organization person - organization - price - disease | 21 | 136_location organization_organization person_organization_price |
| 137 | 14 15 16 - 12 13 14 - 13 14 15 - 11 12 13 - 10 11 12 | 21 | 137_14 15 16_12 13 14_13 14 15_11 12 13 |
| 138 | sports - tech - business - sport - | 21 | 138_sports_tech_business_sport |
| 139 | disorder - body - patient - age - disease | 20 | 139_disorder_body_patient_age |
| 140 | sad - dis - sur - joy - | 20 | 140_sad_dis_sur_joy |
| 141 | healthy - - - - | 20 | 141_healthy___ |
| 142 | drink - tea - wine - coffee - soft | 20 | 142_drink_tea_wine_coffee |
| 143 | protein - chemical - cell - - | 20 | 143_protein_chemical_cell_ |
| 144 | rna - - - - | 20 | 144_rna___ |
| 145 | normal - covid - - - | 20 | 145_normal_covid__ |
| 146 | ex - pt - - - | 20 | 146_ex_pt__ |
| 147 | ok - ft - year - int - rel | 20 | 147_ok_ft_year_int |
| 148 | header - currency - item - zip - state | 20 | 148_header_currency_item_zip |
| 149 | label_122 label_123 - label_123 - label_122 - label_121 - label_120 | 19 | 149_label_122 label_123_label_123_label_122_label_121 |
| 150 | anger disgust - anger disgust fear - disgust fear - disgust - sadness surprise | 19 | 150_anger disgust_anger disgust fear_disgust fear_disgust |
| 151 | na - nn - ft - dis - bio | 19 | 151_na_nn_ft_dis |
| 152 | angry - happy - sad - happy neutral - neutral | 19 | 152_angry_happy_sad_happy neutral |
| 153 | organization percent person - organization percent - miscellaneous - percent person - percent | 19 | 153_organization percent person_organization percent_miscellaneous_percent person |
| 154 | paper - metal - glass - tray - ticket | 19 | 154_paper_metal_glass_tray |
| 155 | mask - normal - sharp - head - green | 19 | 155_mask_normal_sharp_head |
| 156 | noun num pron - num pron propn - pron propn punct - num pron - adj adp adv | 18 | 156_noun num pron_num pron propn_pron propn punct_num pron |
| 157 | answer - - - - | 18 | 157_answer___ |
| 158 | review - id - job - email - state | 18 | 158_review_id_job_email |
| 159 | seven - queen - jack - king - war | 18 | 159_seven_queen_jack_king |
| 160 | neg - nan - good - - | 18 | 160_neg_nan_good_ |
| 161 | ii - blank - vi - et - lower | 18 | 161_ii_blank_vi_et |
| 162 | golden - husky - samoyed - pug - german | 17 | 162_golden_husky_samoyed_pug |
| 163 | arg - delete - act - neg - lead | 17 | 163_arg_delete_act_neg |
| 164 | exp - pp - intj - punc - prep | 17 | 164_exp_pp_intj_punc |
| 165 | email - form - letter - report - news | 17 | 165_email_form_letter_report |
| 166 | protein - rna - cell - line - type | 17 | 166_protein_rna_cell_line |
| 167 | en - hi - fur - - | 17 | 167_en_hi_fur_ |
| 168 | - - - - | 17 | 168____ |
| 169 | - - - - | 17 | 169____ |
| 170 | loc loc - loc - pers - evt - | 16 | 170_loc loc_loc_pers_evt |
| 171 | menu - - - - | 16 | 171_menu___ |
| 172 | normal - - - - | 16 | 172_normal___ |
| 173 | label_122 label_123 - label_97 label_98 label_99 - label_97 label_98 - label_96 label_97 label_98 - label_98 label_99 | 16 | 173_label_122 label_123_label_97 label_98 label_99_label_97 label_98_label_96 label_97 label_98 |
| 174 | cell - organ - organism - tissue - disease | 16 | 174_cell_organ_organism_tissue |
| 175 | target - instrument - opinion - price - product | 16 | 175_target_instrument_opinion_price |
| 176 | org org - org org org - loc loc - org - prs | 16 | 176_org org_org org org_loc loc_org |
| 177 | 10 11 - 10 11 12 - 11 12 - 12 - 11 | 16 | 177_10 11_10 11 12_11 12_12 |
| 178 | korean - russian - dutch - persian - french | 16 | 178_korean_russian_dutch_persian |
| 179 | label_4 label_40 label_41 - label_39 label_4 label_40 - label_38 label_39 label_4 - label_37 label_38 label_39 - label_40 label_41 | 16 | 179_label_4 label_40 label_41_label_39 label_4 label_40_label_38 label_39 label_4_label_37 label_38 label_39 |
| 180 | experience - location - loc misc org - loc misc - misc org | 15 | 180_experience_location_loc misc org_loc misc |
| 181 | normal - pressure - high - water - | 15 | 181_normal_pressure_high_water |
| 182 | company - institution - loc org - degree - org | 15 | 182_company_institution_loc org_degree |
| 183 | short - sl - long - - | 15 | 183_short_sl_long_ |
| 184 | good - bad - non - - | 15 | 184_good_bad_non_ |
| 185 | 149 - 151 - 191 - 199 - 231 | 15 | 185_149_151_191_199 |
| 186 | unknown - vi - ii - - | 15 | 186_unknown_vi_ii_ |
| 187 | end - head - cross - - | 15 | 187_end_head_cross_ |
| 188 | forest - street - road - tree - mountain | 15 | 188_forest_street_road_tree |
| 189 | label_7 label_8 label_9 - label_8 label_9 - label_0 label_1 label_10 - label_1 label_10 - label_10 | 14 | 189_label_7 label_8 label_9_label_8 label_9_label_0 label_1 label_10_label_1 label_10 |
| 190 | prod - loc - evt - org org - loc loc | 14 | 190_prod_loc_evt_org org |
| 191 | tech - business - sports - science - female | 14 | 191_tech_business_sports_science |
| 192 | adult - child - young - - | 14 | 192_adult_child_young_ |
| 193 | human - organism - plants - - | 14 | 193_human_organism_plants_ |
| 194 | hot dog - chicken - hot - food - dog | 14 | 194_hot dog_chicken_hot_food |
| 195 | rain - snow - - - | 14 | 195_rain_snow__ |
| 196 | objective - neutral - - - | 14 | 196_objective_neutral__ |
| 197 | pro - neutral - russian - attack - | 14 | 197_pro_neutral_russian_attack |
| 198 | normal - disorder - good - - | 14 | 198_normal_disorder_good_ |
| 199 | road - good - bike - - | 14 | 199_road_good_bike_ |
| 200 | - - - - | 14 | 200____ |
| 201 | science - energy - arts - nuclear - systems | 13 | 201_science_energy_arts_nuclear |
| 202 | - - - - | 13 | 202____ |
| 203 | event - ticket - ok - loose - non | 13 | 203_event_ticket_ok_loose |
| 204 | neutral - left - right - unknown - | 13 | 204_neutral_left_right_unknown |
| 205 | - - - - | 13 | 205____ |
| 206 | crime - pers - time - book - org | 13 | 206_crime_pers_time_book |
| 207 | seven - start - record - zero - open | 13 | 207_seven_start_record_zero |
| 208 | label_5 label_50 label_51 - label_50 label_51 label_52 - label_51 label_52 label_53 - label_51 label_52 - label_50 label_51 | 13 | 208_label_5 label_50 label_51_label_50 label_51 label_52_label_51 label_52 label_53_label_51 label_52 |
| 209 | label_29 label_3 label_30 - label_26 label_27 label_28 - label_27 label_28 label_29 - label_27 label_28 - label_28 label_29 label_3 | 13 | 209_label_29 label_3 label_30_label_26 label_27 label_28_label_27 label_28 label_29_label_27 label_28 |
| 210 | human - machine - - - | 13 | 210_human_machine__ |
| 211 | control - la - sin - social - ambient | 13 | 211_control_la_sin_social |
| 212 | anger fear - sadness - anger - fear - fear joy | 13 | 212_anger fear_sadness_anger_fear |
| 213 | panda - ticket - air - bamboo - el | 13 | 213_panda_ticket_air_bamboo |
| 214 | target - - - - | 13 | 214_target___ |
| 215 | id - container - type - person - number | 12 | 215_id_container_type_person |
| 216 | neutral - positive - negative - neutral positive - positive negative | 12 | 216_neutral_positive_negative_neutral positive |
| 217 | change - bad - movement - work - science | 12 | 217_change_bad_movement_work |
| 218 | rust - - - - | 12 | 218_rust___ |
| 219 | quantity - container - package - id - weight | 12 | 219_quantity_container_package_id |
| 220 | text - - - - | 12 | 220_text___ |
| 221 | background - objective - - - | 12 | 221_background_objective__ |
| 222 | middle - subject - yes - request - answer | 12 | 222_middle_subject_yes_request |
| 223 | - - - - | 12 | 223____ |
| 224 | public - ambiguous - non - person - | 12 | 224_public_ambiguous_non_person |
| 225 | healthy - plant - pepper - spot - leaf | 12 | 225_healthy_plant_pepper_spot |
| 226 | punc - prep - digit - latin - conj | 12 | 226_punc_prep_digit_latin |
| 227 | location money - language - percent person - actor - money | 12 | 227_location money_language_percent person_actor |
| 228 | - - - - | 11 | 228____ |
| 229 | punc - zero - pers - neg - reflex | 11 | 229_punc_zero_pers_neg |
| 230 | album - major - copper - coon - common | 11 | 230_album_major_copper_coon |
| 231 | metal - pop - country - dance - hip | 11 | 231_metal_pop_country_dance |
| 232 | energy - common - grass - persian - removal | 11 | 232_energy_common_grass_persian |
| 233 | man - double - bird - long - single | 11 | 233_man_double_bird_long |
| 234 | 17 - 16 - 18 - 13 - 15 | 11 | 234_17_16_18_13 |
| 235 | email - actor - threat - tools - attack | 11 | 235_email_actor_threat_tools |
| 236 | space - - - - | 11 | 236_space___ |
| 237 | type - country - jeep - van - lincoln | 11 | 237_type_country_jeep_van |
| 238 | general - - - - | 10 | 238_general___ |
| 239 | ru - mat - - - | 10 | 239_ru_mat__ |
| 240 | contradiction - non - entailment - neutral - | 10 | 240_contradiction_non_entailment_neutral |
| 241 | city - new - country - location - label_1 | 10 | 241_city_new_country_location |
| 242 | non - legal - sub - - | 9 | 242_non_legal_sub_ |
| 243 | tulip - cattle - motorcycle - road - color | 8 | 243_tulip_cattle_motorcycle_road |
| 244 | item - color - cc - model - | 8 | 244_item_color_cc_model |
| 245 | delivery - product - service - different - environment | 7 | 245_delivery_product_service_different |
| 246 | degree - tim - neg - pos - propn | 6 | 246_degree_tim_neg_pos |
| 247 | threat - hate - non - unknown - neutral | 6 | 247_threat_hate_non_unknown |
| 248 | label_33 label_34 - label_32 label_33 label_34 - label_32 label_33 - label_31 label_32 label_33 - label_31 label_32 | 6 | 248_label_33 label_34_label_32 label_33 label_34_label_32 label_33_label_31 label_32 label_33 |
| 249 | experience - location - - - | 6 | 249_experience_location__ |
| 250 | nat - gpe - geo - pro - tim | 5 | 250_nat_gpe_geo_pro |
</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
|