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train

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The dataset generation failed

Error code:   DatasetGenerationError
Exception:    DatasetGenerationError
Message:      An error occurred while generating the dataset
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1279, in compute_config_parquet_and_info_response
                  fill_builder_info(builder, hf_endpoint=hf_endpoint, hf_token=hf_token, validate=validate)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 707, in fill_builder_info
                  ) = retry_validate_get_features_num_examples_size_and_compression_ratio(
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 626, in retry_validate_get_features_num_examples_size_and_compression_ratio
                  validate(pf)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 664, in validate
                  raise TooBigRowGroupsError(
              worker.job_runners.config.parquet_and_info.TooBigRowGroupsError: Parquet file has too big row groups. First row group has 498344255 which exceeds the limit of 300000000
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1995, in _prepare_split_single
                  for _, table in generator:
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 818, in wrapped
                  for item in generator(*args, **kwargs):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 97, in _generate_tables
                  yield f"{file_idx}_{batch_idx}", self._cast_table(pa_table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 75, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              user_id: int64
              feature_0: double
              feature_1: double
              feature_2: double
              feature_3: double
              feature_4: double
              feature_5: double
              feature_6: double
              feature_7: double
              feature_8: double
              feature_9: double
              feature_10: double
              feature_11: double
              feature_12: double
              feature_13: double
              feature_14: double
              feature_15: double
              feature_16: double
              feature_17: double
              feature_18: double
              feature_19: double
              feature_20: double
              feature_21: double
              feature_22: double
              feature_23: double
              feature_24: double
              feature_25: double
              feature_26: double
              feature_27: double
              feature_28: double
              feature_29: double
              feature_30: double
              feature_31: double
              feature_32: double
              feature_33: double
              feature_34: double
              feature_35: double
              feature_36: double
              feature_37: double
              feature_38: double
              feature_39: double
              feature_40: double
              feature_41: double
              feature_42: double
              feature_43: double
              feature_44: double
              feature_45: double
              feature_46: double
              feature_47: double
              feature_48: double
              feature_49: double
              feature_50: double
              feature_51: double
              feature_52: double
              feature_53: double
              feature_54: double
              feature_55: double
              feature_56: double
              feature_57: double
              feature_58: double
              feature_59: double
              feature_60: double
              feature_61: double
              feature_62: double
              feature_63: double
              feature_64: double
              feature_65: double
              feature_66: double
              feature_67: double
              feature_68: double
              feature_69: double
              feature_70: double
              feature_71: double
              feature_72: double
              feature_73: double
              feature_74: double
              feature_75: double
              feature_76: double
              feature_77: double
              feature_78: d
              ...
              ure_186: double
              feature_187: double
              feature_188: double
              feature_189: double
              feature_190: double
              feature_191: double
              feature_192: double
              feature_193: double
              feature_194: double
              feature_195: double
              feature_196: double
              feature_197: double
              feature_198: double
              feature_199: double
              feature_200: double
              feature_201: double
              feature_202: double
              feature_203: double
              feature_204: double
              feature_205: double
              feature_206: double
              feature_207: double
              feature_208: double
              feature_209: double
              feature_210: double
              feature_211: double
              feature_212: double
              feature_213: double
              feature_214: double
              feature_215: double
              feature_216: double
              feature_217: double
              feature_218: double
              feature_219: double
              feature_220: double
              feature_221: double
              feature_222: double
              feature_223: double
              feature_224: double
              feature_225: double
              feature_226: double
              feature_227: double
              feature_228: double
              feature_229: double
              feature_230: double
              feature_231: double
              feature_232: double
              feature_233: double
              feature_234: double
              feature_235: double
              feature_236: double
              feature_237: double
              feature_238: double
              feature_239: double
              feature_240: double
              feature_241: double
              feature_242: double
              feature_243: double
              feature_244: double
              feature_245: double
              feature_246: double
              feature_247: double
              feature_248: double
              feature_249: double
              feature_250: double
              feature_251: double
              feature_252: double
              feature_253: double
              feature_254: double
              feature_255: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 31642
              to
              {'user_id': Value(dtype='int64', id=None), 'feature_0': Value(dtype='float64', id=None), 'feature_1': Value(dtype='float64', id=None), 'feature_2': Value(dtype='float64', id=None), 'feature_3': Value(dtype='float64', id=None), 'feature_4': Value(dtype='float64', id=None), 'feature_5': Value(dtype='float64', id=None), 'feature_6': Value(dtype='float64', id=None), 'feature_7': Value(dtype='float64', id=None), 'feature_8': Value(dtype='float64', id=None), 'feature_9': Value(dtype='float64', id=None), 'feature_10': Value(dtype='float64', id=None), 'feature_11': Value(dtype='float64', id=None), 'feature_12': Value(dtype='float64', id=None), 'feature_13': Value(dtype='float64', id=None), 'feature_14': Value(dtype='float64', id=None), 'feature_15': Value(dtype='float64', id=None), 'feature_16': Value(dtype='float64', id=None), 'feature_17': Value(dtype='float64', id=None), 'feature_18': Value(dtype='float64', id=None), 'feature_19': Value(dtype='float64', id=None), 'feature_20': Value(dtype='float64', id=None), 'feature_21': Value(dtype='float64', id=None), 'feature_22': Value(dtype='float64', id=None), 'feature_23': Value(dtype='float64', id=None), 'feature_24': Value(dtype='float64', id=None), 'feature_25': Value(dtype='float64', id=None), 'feature_26': Value(dtype='float64', id=None), 'feature_27': Value(dtype='float64', id=None), 'feature_28': Value(dtype='float64', id=None), 'feature_29': Value(dtype='float64', id=None), 'feature_30': Value(dtype='float64', id=None), 'feature_3
              ...
              ', id=None), 'feature_481': Value(dtype='float64', id=None), 'feature_482': Value(dtype='float64', id=None), 'feature_483': Value(dtype='float64', id=None), 'feature_484': Value(dtype='float64', id=None), 'feature_485': Value(dtype='float64', id=None), 'feature_486': Value(dtype='float64', id=None), 'feature_487': Value(dtype='float64', id=None), 'feature_488': Value(dtype='float64', id=None), 'feature_489': Value(dtype='float64', id=None), 'feature_490': Value(dtype='float64', id=None), 'feature_491': Value(dtype='float64', id=None), 'feature_492': Value(dtype='float64', id=None), 'feature_493': Value(dtype='float64', id=None), 'feature_494': Value(dtype='float64', id=None), 'feature_495': Value(dtype='float64', id=None), 'feature_496': Value(dtype='float64', id=None), 'feature_497': Value(dtype='float64', id=None), 'feature_498': Value(dtype='float64', id=None), 'feature_499': Value(dtype='float64', id=None), 'feature_500': Value(dtype='float64', id=None), 'feature_501': Value(dtype='float64', id=None), 'feature_502': Value(dtype='float64', id=None), 'feature_503': Value(dtype='float64', id=None), 'feature_504': Value(dtype='float64', id=None), 'feature_505': Value(dtype='float64', id=None), 'feature_506': Value(dtype='float64', id=None), 'feature_507': Value(dtype='float64', id=None), 'feature_508': Value(dtype='float64', id=None), 'feature_509': Value(dtype='float64', id=None), 'feature_510': Value(dtype='float64', id=None), 'feature_511': Value(dtype='float64', id=None)}
              because column names don't match
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1292, in compute_config_parquet_and_info_response
                  parquet_operations, partial = stream_convert_to_parquet(
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 909, in stream_convert_to_parquet
                  builder._prepare_split(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2038, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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float64	feature_52 float64	feature_53 float64	feature_54 float64	feature_55 float64	feature_56 float64	feature_57 float64	feature_58 float64	feature_59 float64	feature_60 float64	feature_61 float64	feature_62 float64	feature_63 float64	feature_64 float64	feature_65 float64	feature_66 float64	feature_67 float64	feature_68 float64	feature_69 float64	feature_70 float64	feature_71 float64	feature_72 float64	feature_73 float64	feature_74 float64	feature_75 float64	feature_76 float64	feature_77 float64	feature_78 float64	feature_79 float64	feature_80 float64	feature_81 float64	feature_82 float64	feature_83 float64	feature_84 float64	feature_85 float64	feature_86 float64	feature_87 float64	feature_88 float64	feature_89 float64	feature_90 float64	feature_91 float64	feature_92 float64	feature_93 float64	feature_94 float64	feature_95 float64	feature_96 float64	feature_97 float64	feature_98 float64	feature_99 float64	feature_100 float64	feature_101 float64	feature_102 float64	feature_103 float64	feature_104 float64	feature_105 float64	feature_106 float64	feature_107 float64	feature_108 float64	feature_109 float64	feature_110 float64	feature_111 float64	feature_112 float64	feature_113 float64	feature_114 float64	feature_115 float64	feature_116 float64	feature_117 float64	feature_118 float64	feature_119 float64	feature_120 float64	feature_121 float64	feature_122 float64	feature_123 float64	feature_124 float64	feature_125 float64	feature_126 float64	feature_127 float64	feature_128 float64	feature_129 float64	feature_130 float64	feature_131 float64	feature_132 float64	feature_133 float64	feature_134 float64	feature_135 float64	feature_136 float64	feature_137 float64	feature_138 float64	feature_139 float64	feature_140 float64	feature_141 float64	feature_142 float64	feature_143 float64	feature_144 float64	feature_145 float64	feature_146 float64	feature_147 float64	feature_148 float64	feature_149 float64	feature_150 float64	feature_151 float64	feature_152 float64	feature_153 float64	feature_154 float64	feature_155 float64	feature_156 float64	feature_157 float64	feature_158 float64	feature_159 float64	feature_160 float64	feature_161 float64	feature_162 float64	feature_163 float64	feature_164 float64	feature_165 float64	feature_166 float64	feature_167 float64	feature_168 float64	feature_169 float64	feature_170 float64	feature_171 float64	feature_172 float64	feature_173 float64	feature_174 float64	feature_175 float64	feature_176 float64	feature_177 float64	feature_178 float64	feature_179 float64	feature_180 float64	feature_181 float64	feature_182 float64	feature_183 float64	feature_184 float64	feature_185 float64	feature_186 float64	feature_187 float64	feature_188 float64	feature_189 float64	feature_190 float64	feature_191 float64	feature_192 float64	feature_193 float64	feature_194 float64	feature_195 float64	feature_196 float64	feature_197 float64	feature_198 float64	feature_199 float64	feature_200 float64	feature_201 float64	feature_202 float64	feature_203 float64	feature_204 float64	feature_205 float64	feature_206 float64	feature_207 float64	feature_208 float64	feature_209 float64	feature_210 float64	feature_211 float64	feature_212 float64	feature_213 float64	feature_214 float64	feature_215 float64	feature_216 float64	feature_217 float64	feature_218 float64	feature_219 float64	feature_220 float64	feature_221 float64	feature_222 float64	feature_223 float64	feature_224 float64	feature_225 float64	feature_226 float64	feature_227 float64	feature_228 float64	feature_229 float64	feature_230 float64	feature_231 float64	feature_232 float64	feature_233 float64	feature_234 float64	feature_235 float64	feature_236 float64	feature_237 float64	feature_238 float64	feature_239 float64	feature_240 float64	feature_241 float64	feature_242 float64	feature_243 float64	feature_244 float64	feature_245 float64	feature_246 float64	feature_247 float64	feature_248 float64	feature_249 float64	feature_250 float64	feature_251 float64	feature_252 float64	feature_253 float64	feature_254 float64	feature_255 float64	feature_256 float64	feature_257 float64	feature_258 float64	feature_259 float64	feature_260 float64	feature_261 float64	feature_262 float64	feature_263 float64	feature_264 float64	feature_265 float64	feature_266 float64	feature_267 float64	feature_268 float64	feature_269 float64	feature_270 float64	feature_271 float64	feature_272 float64	feature_273 float64	feature_274 float64	feature_275 float64	feature_276 float64	feature_277 float64	feature_278 float64	feature_279 float64	feature_280 float64	feature_281 float64	feature_282 float64	feature_283 float64	feature_284 float64	feature_285 float64	feature_286 float64	feature_287 float64	feature_288 float64	feature_289 float64	feature_290 float64	feature_291 float64	feature_292 float64	feature_293 float64	feature_294 float64	feature_295 float64	feature_296 float64	feature_297 float64	feature_298 float64	feature_299 float64	feature_300 float64	feature_301 float64	feature_302 float64	feature_303 float64	feature_304 float64	feature_305 float64	feature_306 float64	feature_307 float64	feature_308 float64	feature_309 float64	feature_310 float64	feature_311 float64	feature_312 float64	feature_313 float64	feature_314 float64	feature_315 float64	feature_316 float64	feature_317 float64	feature_318 float64	feature_319 float64	feature_320 float64	feature_321 float64	feature_322 float64	feature_323 float64	feature_324 float64	feature_325 float64	feature_326 float64	feature_327 float64	feature_328 float64	feature_329 float64	feature_330 float64	feature_331 float64	feature_332 float64	feature_333 float64	feature_334 float64	feature_335 float64	feature_336 float64	feature_337 float64	feature_338 float64	feature_339 float64	feature_340 float64	feature_341 float64	feature_342 float64	feature_343 float64	feature_344 float64	feature_345 float64	feature_346 float64	feature_347 float64	feature_348 float64	feature_349 float64	feature_350 float64	feature_351 float64	feature_352 float64	feature_353 float64	feature_354 float64	feature_355 float64	feature_356 float64	feature_357 float64	feature_358 float64	feature_359 float64	feature_360 float64	feature_361 float64	feature_362 float64	feature_363 float64	feature_364 float64	feature_365 float64	feature_366 float64	feature_367 float64	feature_368 float64	feature_369 float64	feature_370 float64	feature_371 float64	feature_372 float64	feature_373 float64	feature_374 float64	feature_375 float64	feature_376 float64	feature_377 float64	feature_378 float64	feature_379 float64	feature_380 float64	feature_381 float64	feature_382 float64	feature_383 float64	feature_384 float64	feature_385 float64	feature_386 float64	feature_387 float64	feature_388 float64	feature_389 float64	feature_390 float64	feature_391 float64	feature_392 float64	feature_393 float64	feature_394 float64	feature_395 float64	feature_396 float64	feature_397 float64	feature_398 float64	feature_399 float64	feature_400 float64	feature_401 float64	feature_402 float64	feature_403 float64	feature_404 float64	feature_405 float64	feature_406 float64	feature_407 float64	feature_408 float64	feature_409 float64	feature_410 float64	feature_411 float64	feature_412 float64	feature_413 float64	feature_414 float64	feature_415 float64	feature_416 float64	feature_417 float64	feature_418 float64	feature_419 float64	feature_420 float64	feature_421 float64	feature_422 float64	feature_423 float64	feature_424 float64	feature_425 float64	feature_426 float64	feature_427 float64	feature_428 float64	feature_429 float64	feature_430 float64	feature_431 float64	feature_432 float64	feature_433 float64	feature_434 float64	feature_435 float64	feature_436 float64	feature_437 float64	feature_438 float64	feature_439 float64	feature_440 float64	feature_441 float64	feature_442 float64	feature_443 float64	feature_444 float64	feature_445 float64	feature_446 float64	feature_447 float64	feature_448 float64	feature_449 float64	feature_450 float64	feature_451 float64	feature_452 float64	feature_453 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9	-0.183629	-0.396438	0.318547	0.252804	-0.153175	0.245289	-0.045683	0.297245	0.409733	0.092204	0.066508	-0.141875	-0.141445	0.18134	0.12886	0.045617	0.052898	0.000202	-0.113885	-0.092104	-0.046777	0.077584	0.008702	0.355238	0.159885	0.04155	-0.148596	0.048994	0.07789	0.161691	-0.072201	0.049136	0.350232	-0.275344	0.144653	0.10448	-0.055855	0.17448	-0.15695	-0.035289	-0.259476	-0.135787	0.139261	0.312278	-0.331438	0.055766	0.287298	-0.278228	0.022803	0.043005	0.350749	-0.475474	0.125871	-0.11121	0.078993	-0.249074	0.125904	0.46582	0.084984	-0.21644	0.239985	-0.185956	-0.057764	-0.282892	-0.023382	0.011844	0.118262	-0.0484	-0.244715	-0.375247	-0.220468	-0.150376	-0.447772	-0.108977	-0.046408	-0.184405	0.044066	0.036722	0.013635	0.090517	-0.396739	0.298897	0.201039	0.266338	-0.039376	-0.222353	-0.112445	0.1825	-0.170527	-0.403641	0.388413	-0.276883	0.089832	0.492651	-0.018929	0.261132	0.118698	-0.146096	0.134767	-0.007254	-0.072403	0.387621	-0.471168	0.060827	0.051329	0.310347	-0.275078	0.403969	-0.155973	0.044609	-0.275997	0.119956	0.04924	0.193771	0.121615	0.090125	-0.185266	-0.171273	-0.637386	0.074844	-0.182723	-0.253817	0.165278	-0.009178	-0.148173	0.213522	-0.09623	0.245016	-0.059945	0.025509	0.61086	-0.159084	-0.214852	0.317048	0.39767	-0.324309	0.002974	-0.015731	0.107537	0.187315	-0.122795	-0.344446	0.073107	-0.301884	0.182089	0.404207	0.251344	-0.048605	0.001811	0.085376	0.15624	-0.28909	0.369803	-0.408019	0.093614	0.264768	-0.335368	-0.030376	-0.055992	-0.485243	-0.022559	0.218422	0.260243	-0.14468	0.238656	0.228267	-0.000449	0.242494	-0.102241	-0.294901	-0.271733	-0.025768	-0.072134	-0.078052	-0.330698	0.151161	0.082228	-0.440789	-0.166693	0.41576	0.373131	0.237929	-0.290591	0.010276	-0.103328	0.179638	-0.396251	-0.025248	0.205313	-0.004804	0.180789	0.176918	-0.236707	-0.125595	0.078045	0.021201	-0.110571	0.030519	0.003547	-0.489678	0.252313	0.081724	-0.089115	-0.090844	-0.233772	-0.180599	-0.038129	-0.127907	-0.009965	-0.200874	0.106179	-0.024456	-0.509577	0.019635	0.21955	0.245074	0.016859	-0.02486	0.054093	-0.127691	0.128475	-0.13526	0.237692	-0.066995	-0.056572	0.163548	0.397366	0.163802	-0.106895	-0.236826	-0.231145	0.298373	-0.214118	0.199921	0.207346	0.049284	0.266318	-0.114111	-0.248975	0.37402	-0.31294	-0.161547	0.073403	-0.066347	-0.000279	-0.04744	-0.016056	0.25944	-0.169688	0.07271	-0.294301	0.189522	0.136195	0.044768	-0.003588	0.266265	0.122098	-0.045094	-0.22229	0.030285	0.233557	-0.082379	0.334548	-0.216715	0.149579	0.123743	-0.112288	-0.017164	-0.034703	0.109002	-0.204818	-0.376667	-0.252266	-0.391273	0.090574	0.262358	-0.390783	0.147069	-0.340435	-0.327754	0.441216	0.170903	0.130667	-0.1765	-0.026543	-0.308955	-0.245195	-0.501169	0.262659	0.130075	0.108556	-0.132346	0.158282	0.361739	-0.01564	-0.320515	-0.355697	0.387999	-0.323539	-0.148905	0.277876	0.028938	0.528898	-0.18656	0.103121	-0.017939	0.00751	0.06453	0.225757	0.032353	0.137521	-0.372864	-0.145117	0.062901	-0.363685	0.21727	0.33499	0.074105	-0.158764	0.449885	0.124317	0.358419	0.457206	0.146628	0.183474	-0.082367	0.246458	-0.194222	0.373624	0.319476	0.337676	0.11313	0.258422	0.22817	-0.124756	-0.215282	-0.038374	0.106178	0.264681	0.191634	0.195774	-0.145554	0.195173	-0.429782	-0.102785	-0.281806	0.075745	0.301231	0.125028	-0.322152	0.066131	-0.369205	0.275242	-0.32693	0.310386	-0.416444	-0.303734	-0.157889	0.064625	0.07144	0.163253	-0.095299	0.376646	0.226637	0.22235	0.155387	-0.146962	0.155806	-0.165233	-0.172353	-0.295619	-0.116536	-0.276404	0.285849	0.409833	-0.148551	-0.109952	0.161252	0.078216	-0.247469	-0.011512	-0.322291	-0.488541	0.155888	-0.000319	0.040267	-0.1771	-0.473169	0.05923	0.222895	-0.140352	-0.121112	0.249767	0.204098	-0.02788	-0.1372	-0.370927	0.048544	-0.033622	-0.246395	-0.012793	-0.079209	0.229083	0.103895	-0.151631	-0.157735	0.059623	0.172727	-0.063668	-0.041065	-0.068185	0.048499	-0.442452	0.524427	0.113284	0.463154	0.031039	0.4275	0.31454	0.121789	0.252741	-0.497384	0.11313	0.049204	-0.09488	0.017208	0.043937	0.044701	-0.278983	-0.200264	-0.079161	0.143925	0.205625	-0.375054	-0.20247	0.262161	0.129901	-0.057579	-0.238832	-0.015995	0.253022	-0.037637	0.013002	0.046495	0.26003	-0.113287	0.422444	0.047668	0.249289	-0.220881	-0.267735	0.165396	0.090974	-0.288056	0.019895	-0.216632	0.000932	-0.086057	0.251788	0.059609	-0.080014	-0.258312	0.170677	0.414523	-0.397886	0.087514	-0.04364	0.1877	0.432693	-0.173963	0.156675	0.251454	-0.374353	-0.276451	-0.476831	-0.053035	-0.251373	-0.043209	-0.236412	0.269533	0.09793	0.27929	0.224188	0.021467	-0.398398	-0.146092	-0.025148	-0.178272	0.179004	0.055443	-0.078853	0.289055	-0.007185	-0.075235	-0.150731	-0.297376	-0.178876	0.439593	0.174485	0.017275	-0.421095	0.02406	-0.145974	-0.038575	-0.25489	0.24281	0.318659	-0.131932	0.543532	0.153454	-0.303666	-0.079951
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