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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 1 new columns ({'text'}) and 1 missing columns ({'clean_text'}).

This happened while the csv dataset builder was generating data using

hf://datasets/airzipm/sentiment-dataset/raw/train_raw.csv (at revision d81e797023d7195f05e0406da23ed9983b180e7a), ['hf://datasets/airzipm/sentiment-dataset@d81e797023d7195f05e0406da23ed9983b180e7a/processed/train_clean.csv', 'hf://datasets/airzipm/sentiment-dataset@d81e797023d7195f05e0406da23ed9983b180e7a/raw/train_raw.csv']

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              text: string
              label: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 496
              to
              {'clean_text': Value('string'), 'label': Value('int64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1839, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 1 new columns ({'text'}) and 1 missing columns ({'clean_text'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/airzipm/sentiment-dataset/raw/train_raw.csv (at revision d81e797023d7195f05e0406da23ed9983b180e7a), ['hf://datasets/airzipm/sentiment-dataset@d81e797023d7195f05e0406da23ed9983b180e7a/processed/train_clean.csv', 'hf://datasets/airzipm/sentiment-dataset@d81e797023d7195f05e0406da23ed9983b180e7a/raw/train_raw.csv']
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

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clean_text
string
label
int64
mall go one pretty decent large modern lot popular brand store like movie theater plus several good restaurant near mall
1
lot artist today stock tonight late night shopping haltwhistle glad see sun out ! see later
2
italy tomorrow amazing photo you ! night !
2
dane county fun warm airport although small plenty food drink option business traveler not notice wifi station recharge station
2
think step tomorrow club bodi decision u2019s make
1
would like comment series great effort story line although require improvement pretty well especially season season however become freak show lose da original charm season one story line interesting light side life jam pony focus serious plot manticore chasing series look forward new season fact still hope fox guy da p...
2
strong script powerful direction splendid production design allow we transport life wladyslaw szpilman not pianist good human
2
get old slow tired look inside seem come great patio superb view old montreal painfully sit inside thus experience no view sluggish service waiter pay no interest get anything right food average price high get fail see bad yelp google review place would kept walk expensive slow bar area look old world whole place need ...
0
kris bryant ground 2nd strand dexter fowler foot away cub trail rockie
1
delivery say minute turn minute get food owner apologetic recooke deliver order say new delivery person get lose nthankfully food taste good regained star not sure try location long wait even though food pretty tasty
0
not see yet catch end murray loss light interview svp dude though 1st show
1
genuine scream situation comedy farce mid 70 film huge hit minute disappear face earth constantly amazed comedy film big release one week vanish high anxiety cheap detective black bird not look shoot no profile today norman comedy month whenever everyone seem see laugh never ever mention ever famous shot videotape tran...
2
gucci unmentionable alter good hope december extend match symptomatologic entrance reinforcement til
1
discovery
2
not let dumb name fool good sushi place no new zealand food flair small little place good fresh sushi ! first place charlotte actually really like food far sushi go go know sit close patron able hear everyone talk restaurant staff friendly accommodate towards odd order nice spicy mayo mayoie however spell word go birth...
1
carrie fisher state one occasion make movie period life heavy cocaine problem not remember much would explain make film not explain anyone else cast crew can not believe everybody coke problem one absolute bad movie ever make say something blame can not lay foot director tim kincaid writer buddy giovinazzo obvious pict...
0
since last review oggi october din twice request other times food continue disappoint past friday arrive shortly receive table immediately luckily line start line yes still amaze base food host friendly waiter arrive take drink order go special start calamari zucchini breadly perfectly serve light marinara sauce great ...
0
first host complete douchesnob dare audacity show high caliber dining establishment without make reservation ahead time ? ? excuse good sir restaurant currently quite empty fancy may think place huge 70 music blaring boat park foot away think otherwise yes cleopatra barge actually detract elegance hyakumi seem strive n...
0
attention fan ! ! come worship august 16th gmwa marriott florida ballroom tampa fl 15pm ! not miss it !
2
perfect black pearl
2
nauseate spin credit sequence
0
20th anniversary ps4 controller available much likely go for ?
1
distance
2
type person complain venue soulless characterless lack atmosphere one would think would know not come town leisure complex soullessness requirement complex way benefit look evening can not face thought use brain imagination ncinema chain restaurant bowl casino perfectly dull acceptable
2
muslims come town 1st wave new generation school ish 2nd wave thing get bad
0
actor herman josé play role football soccer entrepreneur acquire pass two african player try sell little money rival club benfica club heart fc porto therefore player not play well want fc port wrong happen two player good fc porto sell much money foreign club make good business film small country portugal without grea...
2
love movie love two family cross path history question sam get kill family line continue ? madame zeroni son zero suppose relate no mention child ? hmmmmmmmmm never mention child wife prior speak fall love teacher ? maybe child prior become kiss kate bandit ? even mistake movie love act great not sure story mr sir mari...
2
one direction go november los angeles bring 1d we ellen give ticket apply
1
margherita pizza thin crust actually not flop fold pick cheese layer sit tangy tomato sauce genovese pizza pesto bring need freshness contrast smokiness turkey despite topping combine interesting profile pesto could not replace good tomato sauce
1
good picture baseball since redford whack natural way dennis quaid rachel griffiths light screen great story cast seem real enough pull life lace dream drip reality american dream reignite true story devil ray mid life rookie jimmy morris australian bear actress rachel griffiths play native west texan well lot texans k...
2
interesting historical study tragic love story
2
get back ohio la see guy wear jersey sun one lax yesterday leahstrong
2
ed harris work film usual standard excellence steal screen away anyone share include formidable sean connery movie bit sanctimonious come alive scene harris interrogate attorney another convict breathtake master class artistic control cast member adept connery reliable fishbourne story pack no wallop plot depend largel...
2
really look forward show give quality actor fact scott brother involve unfortunately hop dash ! yet lead believe kgb group inept moron not clue one point laughable scene kgb agent could not handle one cia agent grow weary biased one side completely inaccurate portrayal spy game go cold war find laughable we incapable m...
0
currentevent poor aaron barr u002c learn anonymous hard way tomorrow look pipa u002c sopa u002c acta
1
almost entirely witless inane carry every gag two three time beyond limit sustain laugh
0
negotiate imperfect love hate relationship
0
badly render cgi effect
0
grade ngreat food loud place prefer not shout dinner
2
oz bar bar student drink drench lifestyle always great bar visit base fact less busy main grassmarket bar especially want queue less min drink ni return old stamp ground catch uk yelp scene australia day hindsight realize choice location close insanity lot happy australian student party like well australia day latecome...
1
michaeljackson die care conrad murray whole 83minute murray call truth come thur
0
watch holly along another movie traffic child sexual exploitation call trade film sea international film festival say holly blow trade water holly powerful amazing film many different level purely artistic cinematic perspective amazing sound mix camera angle direct act spot additionally way handle subject matter tastef...
2
kendrick verse black friday validate leap bound rap nigga right jesus christ
2
flat run
0
morning gorgeous rite think slisten nicki minaj hhave domestic
2
amazing giveaway win book choice book depository
2
not fool not cheese ! nwhen think store dedicated cheese think go place like holiday gift not every day shop but ! store much cheese although cheese selection amazing wine chocolate also serve food wonderful sandwich salad must try nmost importantly sell macaroon macaroon always search delicious sweet colorful macaroon...
2
honestly hate place birthday hat time nthe food taste mediocre staff rude
0
excited go see rise planet ape tonight
2
well suppose know dumb ass promotional lordi motion picture ? mean realize dinosaur costume show time lead singer make appearance hum hard rock hallelujah even though hate song dark floor young autistic girl process sneak hospital protective father rest people particular elevator become momentarily trap arrive floor co...
0
bdsm sub culture los angeles serve backdrop low budget shabbily construct mess plainly vanity piece top bill player celia xavier also produce script perform dual role twin sister vanessa celia question soon develop whether not rather immoderate camera lighting edit pyrotechnic ever reach point connection weak often inc...
0
someone release movie dvd take hallowed place great film time ten twenty year critic film historian look back call film see vapid part lar von trier try revolutionize revitalize international film world masterpiece stand zentropa europa refer outside we one fascinating artistic view bleakness almost psychotic uncertain...
2
something appear lose translation time
0
first let state never actually receive ride company try two separate occasion dispatch team never allow get far major customer service issue reason ever call company phone number easy remember non recent call company happen last night call pay phone cell phone battery die someone answer ring later mumble hello no menti...
0
departure ship sham port abu dhabi time nov 09am utc time arrival departure time vessel approache
1
end slap target audience face shoot foot
0
place really good food service little well would probably come back nyou get seat quick take mins server come back take order another min wait food want order dessert not not want wait another min come neven check take forever not impressed
1
depress life
0
stop last week try sushi nice atmosphere staff friendly order special day roll can not remember name also rock roll roll fresh good average place sushi rate ok
1
mother daughter night 1st niagara pavilion foo fighter go great day ! tomorrow
2
go brother night row good part free guest hotel not probably think pure jet overall well club stil fun lot people crowd look like people fun expect pay drink worth go go free think also go free sign guest list night not group hot girl guy maybe wait around get call eventually get patient
2
no quarter anyone seek pull cohesive story
0
town business decide give place try not fan binge drinking could tolerate horrible service mediocre food hate fast food would probably hit burger king around corner next time hop would great find
0
capable ante movie star charisma
2
impossible listen kendrick lamar black friday listen least time row
2
no one blame home opener loss pacer except lot bad shot 4th ! toronto raptor
0
take yo daughter idea today spend entire day couple hour child play area several hour learn bug bug exhibit museum definitely keep interest make farm garden plot play area create craft bee wriggle dance bee costume put bug theme puppet show look slew preserve bug specimen museum offer much could anticipate would not he...
2
can not wait see sit night metlife big year
2
never really see esther blossom actress even though talent suppose grow
0
decor nice food not never eat much butter life say authentic japanese experience cook put butter everything nshrimp butter nhe could add garlic little bit rosemary lime grass nmeat butter could not even test meat nrice butter no soy sauce ni would not recommend place
0
occasional charm not dismiss
2
ironically sort disposable kitchen sink homage illustrate whole often less sum part today hollywood
0
may question well quite simple look recent situation conversation naruto partook ago simply
1
cool bean try let know end day ! pm fri 22nd moomba
2
transport also one smart
2
wishy washy melodramatic movie show we plenty sturm und drung explain character decision unsatisfactorily
0
enthusiasm
2
not satisfied tri city go fib dr give day heart monitor monitor not work tell dr thing read heart beat even unattached sit kitchen table tell keep use never think replace order stress test result come dr say stress test normal suggest proceed fix corrode artery not would discharge surgery never happen refuse surgery go...
0
whole affair true story not feel incredibly hokey come like hallmark commercial
0
go last night couple friend befor watchin black gold complete almost annual boring task woope brownie cleveland seat upstairs great table upstairs face ellseworth view great watch many fellow burgher imbibe windy sunday afternoon positive experience end well maybe except humorous menu make smile waitress average know t...
0
place family favorite not say good quality food good enough never understand people expect anything fresh healthy fast food place fast food healthy opposite side spectrum ! big believer say get pay nmy go meal piece shrimp chip monster burger plain cheese yummy npete need get time take cash bit funny see pete n00bs ask...
2
distinguish
2
derivative
0
know intended return charlie hebdo may change direction
1
want sat go art park ?
1
favorite saturday sunday morning breakfast spot ni always get speculoo spread one waffle strawberry banana spread consistency peanut butter make biscoff cooky nnot huge fan coffee though would skip grab door commonplace coffee
2
rick cafe watch dese guy jump cliff drink rum runner sun
1
least one story tell
2
join sun top dog southpaw national hot dog day tomorrow noon learn
2
inbetweener movie week today ! ! aaaahhhh ! might wear wellie cinema knee deep clunge
2
paymon must visit every trip las vegas sea dining option paymon relaxing star service exceptional mediterranean food extra plus abundant portion food reasonable price two could easily share entree still leftover well ice tea valley !
2
clever thriller enough unexpected twist keep interest
2
although movie clearly date audience still easily identify plight hapless buster timeless funny underdog tale buster fight unkindly odd three different age stone age roman age moden age play almost character change scenery help we identify different age movie see one early comedic depiction caveman stereotype win love ...
2
hammond may verify not you ? wtf
1
american playwright howard campbell jr play musty obsolescence nick nolte live happily germany actress wife helga noth sheryl lee begin world war ii peak life howard draft american agent john goodman become spy behalf ally forewarn risk job hold howard everything lose find offer irresistible follow death wife end war c...
2
go texas go u002c actually might meet cotton bowl january
1
faulty premise
0
entertainingly reenact historic scandal
2
long overdue review pepe see check enough time warrant cot back place serve good street tacos las vegas great price nonce inside friendly staff good job keep place clean salsa bar stock also always large portion spicy carrot chop radish red salsa nice heat great flavor would take intravenously could something else uniq...
2
squeeze laugh material
2
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