I am currently using English text classification model. I have formatted my training dataset by input and target however the pipeline keeps failing after the creation of the ML Package. Is there any help?
Error: Pipeline failed due to ML Package Issue
Unable to fetch support Id due to: com.UiPath.ml.exception.BaseException: Error while processing unauthorized response headers, WWW-Authenticate header is missing
As per error looks like the columns text and label could not be identified
Can you check the same…like if you have given the dataset properly and if lbels are given properly
Cheers
hi @Anil_G the headers for the train.csv file is “text” and “label” as per the documentation for English text classification. but the error still happens
SUPPORT_ID: Unable to fetch support Id due to: com.UiPath.ml.exception.BaseException: Error while processing unauthorized response headers, WWW-Authenticate header is missing
AI_UNITS_REMAINING: 192269.0
GEO_LOCATION: eus
** ML PACKAGE INFORMATION **
PACKAGE_NAME: MCC_LTC3
ML_PACKAGE_VERSION: 7.0
PROJECT_ID: 3631c4de-a250-4f89-ae1d-28e8aace9714
PACKAGE_ID: 5350cadd-6af0-4fcd-a5f2-3dba54a5d1a4
BASE_PACKAGE_NAME: EnglishTextClassification
BASE_VERSION: 23.10.3.0
** PIPELINE INFORMATION **
RUN_ID: d9db7166-c7ba-4422-9697-bd8a7b4fbd25
STATUS: FAILED
PROCESSOR: CPU
ENVIRONMENT_VARIABLES: [SettingDto(key=BOW.hyperparameter_search.enable, value=True, type=STRING), SettingDto(key=BOW.hyperparameter_search.timeout, value=1800, type=STRING), SettingDto(key=dataset.input_format, value=ai_center, type=STRING), SettingDto(key=dataset.target_column_name, value=annotations.intent.choices, type=STRING), SettingDto(key=BOW.explain_inference, value=False, type=STRING), SettingDto(key=dataset.input_column_name, value=data.text, type=STRING)]
PIPELINE_TYPE: TRAIN_ONLY
PIPELINE_NAME: Training_Pipeline
TRAINING_DATASET_ID: 803308ad-9f4e-4487-94e1-f25098e877fc
EVALUATION_DATASET_ID:
DATA_DIRECTORY: /
EVALUATION_DIRECTORY:
RUN_TIME: Not Completed
** RUN LOGS **
2024-02-27 19:10:34,024 - UiPath_core.trainer_run:main:83 - INFO: Starting training job…
2024-02-27 19:10:34,234 - matplotlib:_get_config_or_cache_dir:543 - WARNING: Matplotlib created a temporary cache directory at /tmp/matplotlib-ffiammoo because the default path (/home/aicenter/.config/matplotlib) is not a writable directory; it is highly recommended to set the MPLCONFIGDIR environment variable to a writable directory, in particular to speed up the import of Matplotlib and to better support multiprocessing.
2024-02-27 19:10:34,490 - matplotlib.font_manager:_load_fontmanager:1578 - INFO: generated new fontManager
2024-02-27 19:10:38,533 - UiPath_core.storage.azure_storage_client:download:118 - INFO: Dataset from bucket folder training-6f1e3c76-3115-4443-857a-b85821314617/3631c4de-a250-4f89-ae1d-28e8aace9714/803308ad-9f4e-4487-94e1-f25098e877fc with size 1 downloaded successfully
2024-02-27 19:10:38,534 - UiPath_core.training_plugin:train_model:130 - INFO: Start model training…
2024-02-27 19:10:38,534 - UiPath_core.training_plugin:initialize_model:124 - INFO: Start model initialization…
2024-02-27 19:10:38,536 - UiPath_core.training_plugin:initialize_model:127 - INFO: Model initialized successfully
2024-02-27 19:10:38,537 - root:read_all_json:17 - INFO: Reading data from /microservice/dataset
2024-02-27 19:10:38,538 - root:read_all_json:17 - INFO: Reading data from /microservice/dataset/test
2024-02-27 19:10:38,540 - root:read_data:55 - INFO: Series(, Name: label, dtype: int64)
2024-02-27 19:10:38,541 - root:read_data:60 - INFO: Train: (0, 2), Test: (0, 2)
2024-02-27 19:10:38,542 - root:train:61 - INFO: Started hyperparameter search …
2024-02-27 19:10:38,547 - UiPath_core.training_plugin:model_run:179 - ERROR: Training failed for pipeline type: TRAIN_ONLY, error: single positional indexer is out-of-bounds
2024-02-27 19:10:38,548 - UiPath_core.trainer_run:main:100 - ERROR: Training Job failed, error: single positional indexer is out-of-bounds
Traceback (most recent call last):
File “/home/aicenter/.local/lib/python3.9/site-packages/UiPath_core/trainer_run.py”, line 95, in main
wrapper.run()
File “/microservice/training_wrapper.py”, line 58, in run
return self.training_plugin.model_run()
File “/home/aicenter/.local/lib/python3.9/site-packages/UiPath_core/training_plugin.py”, line 195, in model_run
raise ex
File “/home/aicenter/.local/lib/python3.9/site-packages/UiPath_core/training_plugin.py”, line 171, in model_run
self.run_train_only()
File “/home/aicenter/.local/lib/python3.9/site-packages/UiPath_core/training_plugin.py”, line 255, in run_train_only
self.train_model(self.local_dataset_directory)
File “/home/aicenter/.local/lib/python3.9/site-packages/UiPath_core/training_plugin.py”, line 132, in train_model
response = self.model.train(directory)
File “/microservice/train.py”, line 53, in train
train.train(self.opt, self.df_train, self.df_test)
File “”, line 62, in train
File “”, line 154, in hyperparam_search_bow
File “/home/aicenter/.local/lib/python3.9/site-packages/optuna/study/study.py”, line 451, in optimize
_optimize(
File “/home/aicenter/.local/lib/python3.9/site-packages/optuna/study/_optimize.py”, line 66, in _optimize
_optimize_sequential(
File “/home/aicenter/.local/lib/python3.9/site-packages/optuna/study/_optimize.py”, line 163, in _optimize_sequential
frozen_trial = _run_trial(study, func, catch)
File “/home/aicenter/.local/lib/python3.9/site-packages/optuna/study/_optimize.py”, line 251, in _run_trial
raise func_err
File “/home/aicenter/.local/lib/python3.9/site-packages/optuna/study/_optimize.py”, line 200, in _run_trial
value_or_values = func(trial)
File “”, line 139, in call
File “”, line 12, in train_bow
File “”, line 96, in create_from_dataframes
File “”, line 27, in init
File “/home/aicenter/.local/lib/python3.9/site-packages/pandas/core/indexing.py”, line 1153, in getitem
return self._getitem_axis(maybe_callable, axis=axis)
File “/home/aicenter/.local/lib/python3.9/site-packages/pandas/core/indexing.py”, line 1714, in _getitem_axis
self._validate_integer(key, axis)
File “/home/aicenter/.local/lib/python3.9/site-packages/pandas/core/indexing.py”, line 1647, in _validate_integer
raise IndexError(“single positional indexer is out-of-bounds”)
IndexError: single positional indexer is out-of-bounds
2024-02-27 19:10:38,549 - UiPath_core.trainer_run:main:107 - INFO: Job run stopped.
** AUDIT LOGS **
| SEVERITY | USER | DESCRIPTION | CREATED_ON |
|---|
** AUDIT LOG DETAILS **
SEVERITY: ERROR
CREATED_ON: Tue Feb 27 19:11:41 UTC 2024
LOGS:
Traceback (most recent call last):
File “/home/aicenter/.local/lib/python3.9/site-packages/optuna/study/_optimize.py”, line 200, in _run_trial
value_or_values = func(trial)
File “”, line 139, in call
File “”, line 12, in train_bow
File “”, line 96, in create_from_dataframes
File “”, line 27, in init
File “/home/aicenter/.local/lib/python3.9/site-packages/pandas/core/indexing.py”, line 1153, in getitem
return self._getitem_axis(maybe_callable, axis=axis)
File “/home/aicenter/.local/lib/python3.9/site-packages/pandas/core/indexing.py”, line 1714, in _getitem_axis
self._validate_integer(key, axis)
File “/home/aicenter/.local/lib/python3.9/site-packages/pandas/core/indexing.py”, line 1647, in _validate_integer
2024-02-27 19:10:38,547 - UiPath_core.training_plugin:model_run:179 - ERROR: Training failed for pipeline type: TRAIN_ONLY, error: single positional indexer is out-of-bounds
raise IndexError(“single positional indexer is out-of-bounds”)
IndexError: single positional indexer is out-of-bounds
[W 2024-02-27 19:10:38,547] Trial 0 failed with value None.
2024-02-27 19:10:38,548 - UiPath_core.trainer_run:main:100 - ERROR: Training Job failed, error: single positional indexer is out-of-bounds
Traceback (most recent call last):
File “/home/aicenter/.local/lib/python3.9/site-packages/UiPath_core/trainer_run.py”, line 95, in main
wrapper.run()
File “/microservice/training_wrapper.py”, line 58, in run
return self.training_plugin.model_run()
File “/home/aicenter/.local/lib/python3.9/site-packages/UiPath_core/training_plugin.py”, line 195, in model_run
raise ex
File “/home/aicenter/.local/lib/python3.9/site-packages/UiPath_core/training_plugin.py”, line 171, in model_run
self.run_train_only()
File “/home/aicenter/.local/lib/python3.9/site-packages/UiPath_core/training_plugin.py”, line 255, in run_train_only
self.train_model(self.local_dataset_directory)
File “/home/aicenter/.local/lib/python3.9/site-packages/UiPath_core/training_plugin.py”, line 132, in train_model
response = self.model.train(directory)
File “/microservice/train.py”, line 53, in train
train.train(self.opt, self.df_train, self.df_test)
File “”, line 62, in train
File “”, line 154, in hyperparam_search_bow
File “/home/aicenter/.local/lib/python3.9/site-packages/optuna/study/study.py”, line 451, in optimize
_optimize(
File “/home/aicenter/.local/lib/python3.9/site-packages/optuna/study/_optimize.py”, line 66, in _optimize
_optimize_sequential(
File “/home/aicenter/.local/lib/python3.9/site-packages/optuna/study/_optimize.py”, line 163, in _optimize_sequential
frozen_trial = _run_trial(study, func, catch)
File “/home/aicenter/.local/lib/python3.9/site-packages/optuna/study/_optimize.py”, line 251, in _run_trial
raise func_err
File “/home/aicenter/.local/lib/python3.9/site-packages/optuna/study/_optimize.py”, line 200, in _run_trial
value_or_values = func(trial)
File “”, line 139, in call
File “”, line 12, in train_bow
File “”, line 96, in create_from_dataframes
File “”, line 27, in init
File “/home/aicenter/.local/lib/python3.9/site-packages/pandas/core/indexing.py”, line 1153, in getitem
return self._getitem_axis(maybe_callable, axis=axis)
File “/home/aicenter/.local/lib/python3.9/site-packages/pandas/core/indexing.py”, line 1714, in _getitem_axis
se… (truncated).
can you show the training data
looks like it is wrong or your configuration of parameters in pipeline is wrong
Training failed for pipeline type: TRAIN_ONLY, error: single positional indexer is out-of-bounds
cheers
@Anil_G
here is a subset of the training data.
| input | target |
|---|---|
| TOWN OF SUTTON | 9399 |
| TOWN OF SUTTON*SVC | 9399 |
| WAYNE COUNTY HEALTH DEPT | 9399 |
| ST GEORGE SERBIAN ORTHOD | 8398 |
| ST GEORGE SERBIAN ORTHOD | 8398 |
| CONSULATE OF MEXICO | 9399 |
| GSWO TROOP4633_2023 | 8398 |
| GSWO TROOP2019_2023 | 8398 |
| GSWO TROOP4629_2023 | 8398 |
| GSWO TROOP3389_2023 | 8398 |
| GSACPC TROOP07046 | 8398 |
| GSWO TROOP3148_2023 | 8398 |
| GSWO TROOP3148_2023 | 8398 |
| GSWO TROOP4420 | 8398 |
| GSWO TROOP3160 | 8398 |
| GSWO TROOP3278_2023 | 8398 |
| GSWO TROOP3281_2023 | 8398 |
| GSWO TROOP4686_2023 | 8398 |
| GSWO TROOP4676_2023 | 8398 |
| GSWO TROOP4676_2023 | 8398 |
| N. COCHRAN ATTORNEY AT L | 8111 |
| MECHON TOLDOS YEHUDA | 8398 |
| LAURA’S PLACE | 7297 |
| BAIS HORAAH | 8398 |
Did you use the aicenter format only?
Looks like you are using csv but selected format as ai_center
Cheers
I just copied and pasted from the CSV
I get it is a csv
But as per the parameters…you selected ai_center
ENVIRONMENT_VARIABLES: [SettingDto(key=BOW.hyperparameter_search.enable, value=True, type=STRING), SettingDto(key=BOW.hyperparameter_search.timeout, value=1800, type=STRING), SettingDto(key=dataset.input_format, value=ai_center, type=STRING),
Cheers
This is a snapshot from the CSV file
for the pipeline I created no Environment Variables. is this needed?
Sorry I don’t follow what you mean by selecting AI_Center in parameters
If you see the logs
SettingDto(key=dataset.input_format, value=ai_center, type=STRING),
This is the input format …you need to give it as auto and not ai center
Input and target column name are also to be provided as inputs
Cheers
how would I go about doing this?
is it changing the header in the file?
little confusion between two models
I just did a training and it is successful…can you please try the same…and I see you selected major 2 try with 6
here is a sample csv that is successful
NewData.zip (1.3 KB)
Dataset
cheers
ashokkarale
Anil_G
ppr
Stef_99
J0ska
kishan.savaliya
Meu_Eu_Nando
sesa499170
Hazem_Saleh
RPA_Dev13