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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
queries: int64
candidate_width: int64
full_country_targets: int64
model: string
to
{'query_id': Value('string'), 'target_ids': List(Value('string'))}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 764, in write_table
self.write_rows_on_file() # in case there are buffered rows to write first
~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 663, in write_rows_on_file
self._write_table(table)
~~~~~~~~~~~~~~~~~^^^^^^^
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 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
queries: int64
candidate_width: int64
full_country_targets: int64
model: string
to
{'query_id': Value('string'), 'target_ids': List(Value('string'))}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1850, 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 4 new columns ({'queries', 'full_country_targets', 'candidate_width', 'model'}) and 2 missing columns ({'query_id', 'target_ids'}).
This happened while the json dataset builder was generating data using
hf://datasets/uday-bhatia/amazon-ml-26/cpu_host/amazon-rebuild_code/candidate_full_fitting/diagnostics/expanded_oof/train_abd149214539/candidate_id_sample.json (at revision 8d19feb63f3b2698a396b134293a28ec0e91b60c), ['hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/candidate_full_fitting/diagnostics/expanded_oof/train_9b202ecbc6d4/candidate_id_sample.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/candidate_full_fitting/diagnostics/expanded_oof/train_9b202ecbc6d4/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/candidate_full_fitting/diagnostics/expanded_oof/train_abd149214539/candidate_id_sample.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/candidate_full_fitting/diagnostics/expanded_oof/train_abd149214539/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/candidate_pilot/diagnostics/expanded_oof/train_9b202ecbc6d4/candidate_id_sample.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/candidate_pilot/diagnostics/expanded_oof/train_9b202ecbc6d4/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/candidate_pilot/diagnostics/expanded_oof/train_abd149214539/candidate_id_sample.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/candidate_pilot/diagnostics/expanded_oof/train_abd149214539/ready.json', 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'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/retrieval/A1_sharded/train_abd149214539/shard_0_ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/retrieval/A1_sharded/train_abd149214539/shard_1_ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/retrieval/A1_sharded/train_abd149214539/shard_2_ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/retrieval/A1_sharded/train_abd149214539/shard_3_ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/qwen4_full_20260925/pairs/train_9b202ecbc6d4/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/qwen4_full_20260925/pairs/train_abd149214539/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/round2_20260925/retrieval/frozen/train_9b202ecbc6d4/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/round2_20260925/retrieval/frozen/train_abd149214539/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/round2_20260925/retrieval/lex/train_9b202ecbc6d4/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/round2_20260925/retrieval/lex/train_abd149214539/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/round2_20260925/retrieval/tuned/train_9b202ecbc6d4/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/round2_20260925/retrieval/tuned/train_abd149214539/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/round3_20260925/retrieval/lex/train_9b202ecbc6d4/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/round3_20260925/retrieval/lex/train_abd149214539/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/round4_20260925/retrieval/lex/train_9b202ecbc6d4/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/round4_20260925/retrieval/lex/train_abd149214539/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/run_20260925/retrieval/frozen/train_9b202ecbc6d4/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/run_20260925/retrieval/frozen/train_abd149214539/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/run_20260925/retrieval/lex/train_9b202ecbc6d4/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/run_20260925/retrieval/lex/train_abd149214539/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/run_20260925/retrieval/tuned/train_9b202ecbc6d4/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/run_20260925/retrieval/tuned/train_abd149214539/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/storage_recovery/n3cgyo7b0o_A1_train_9b202ecbc6d4_shard2_1790327134/original_runner.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/storage_recovery/n3cgyo7b0o_A1_train_9b202ecbc6d4_shard2_1790327134/owner.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/storage_recovery/n3cgyo7b0o_A1_train_9b202ecbc6d4_shard2_1790327134/runner.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/storage_recovery/n3cgyo7b0o_encode_A3_name_fold0_train_abd149214539_1790327135/original_runner.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/storage_recovery/n3cgyo7b0o_encode_A3_name_fold0_train_abd149214539_1790327135/owner.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/storage_recovery/n3cgyo7b0o_encode_A3_name_fold0_train_abd149214539_1790327135/runner.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/storage_recovery/naornvgt6b_A1_train_abd149214539_shard0_1790327135/original_runner.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/storage_recovery/naornvgt6b_A1_train_abd149214539_shard0_1790327135/owner.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/storage_recovery/naornvgt6b_A1_train_abd149214539_shard0_1790327135/runner.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/storage_recovery/nrvyuynzhj_train_A2_fold1_1790327135/original_runner.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/storage_recovery/nrvyuynzhj_train_A2_fold1_1790327135/owner.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/storage_recovery/nrvyuynzhj_train_A2_fold1_1790327135/runner.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/storage_recovery/nrvyuynzhj_train_A2_fold1_1790327135/train_A2_fold1.1.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/storage_recovery/nrvyuynzhj_train_B2_fold0_1790327135/original_runner.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/storage_recovery/nrvyuynzhj_train_B2_fold0_1790327135/owner.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/storage_recovery/nrvyuynzhj_train_B2_fold0_1790327135/runner.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/workspace/backups/submission-recovery/metadata/runs/fullscale_20260925/storage_recovery/nrvyuynzhj_train_B2_fold0_1790327135/train_B2_fold0.2.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/vm_archive/control_vm/large_files/mnt/amazon-archive/replacement_exchange/exports/training_inputs/train.jsonl', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/owner_shortlist_training/progress.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/owner_shortlist_training/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/matched_report.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/package_manifest.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/partial_manifest.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/progress.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/ready.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/wide_reader_union10_eval_step1000.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/wide_reader_union10_eval_step10000.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/wide_reader_union10_eval_step15000.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/wide_reader_union10_eval_step20000.json', 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'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/wide_reader_union50_eval_step15000.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/wide_reader_union50_eval_step20000.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/wide_reader_union50_eval_step250.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/wide_reader_union50_eval_step25000.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/wide_reader_union50_eval_step30000.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/wide_reader_union50_eval_step35000.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/wide_reader_union50_eval_step40000.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/wide_reader_union50_eval_step45000.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/wide_reader_union50_eval_step45801.json', 'hf://datasets/uday-bhatia/amazon-ml-26@8d19feb63f3b2698a396b134293a28ec0e91b60c/cpu_host/amazon-rebuild_code/wide_reader_training/wide_reader_union50_eval_step5000.json']
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)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1869, in _prepare_split_single
num_examples, num_bytes = writer.finalize()
~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 781, in finalize
self.write_rows_on_file()
~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 663, in write_rows_on_file
self._write_table(table)
~~~~~~~~~~~~~~~~~^^^^^^^
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 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
queries: int64
candidate_width: int64
full_country_targets: int64
model: string
to
{'query_id': Value('string'), 'target_ids': List(Value('string'))}
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 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 1694, 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 1880, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
query_id string | target_ids list |
|---|---|
S1-377745466 | [
"S2-203037501",
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"S2-292889194... |
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S1-22305073 | [
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"S2-92055727... |
S1-504790211 | [
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"S2-349739... |
S1-626914593 | [
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"S2-885601911... |
S1-765734254 | [
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"S2-499761983",
"S2-23401454... |
S1-309349399 | [
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"S3-711170554",
"S3-747914416",
"S3-560833877",
"S2-31204536... |
S1-661315962 | [
"S2-906228400",
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"S3-558516991",
"S3-173691513",
"S2-624425142",
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"S3-690086354",
"S3-569954805",
"S3-273069289",
"S2-473212308",
"S2-862471994",
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"S3-46902220",
"S2-578401926",
"S3-988984511",
"S3-351275036",
"S2-58557800... |
S1-404435514 | [
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"S2-395304119",
"S2-793014991",
"S3-45880278... |
S1-252242682 | [
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"S2-22018566",
"S3-34385234",
"S2-41989751",
"S3-834417519... |
S1-883973644 | [
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"S3-615250031",
"S2-8848826... |
S1-17666546 | [
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"S2-341313901",
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"S2-5059665... |
S1-602913883 | [
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"S3-1786762",
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"S3-778055639",
"S2-3845644",
"S2-620967390",
... |
S1-796227187 | [
"S2-356053713",
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"S3-474797716",
"S3-632380009",
"S3-231084848... |
S1-945437722 | [
"S3-570426744",
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"S3-825670041",
"S3-500057867",
"S2-558426783",
"S2-795988126",
"S2-6283256... |
S1-976369483 | [
"S2-896291492",
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"S2-552765718",
"S2-126181351",
"S3-435391981",
"S3-296705189",
"S3-869682... |
S1-370715897 | [
"S2-146449836",
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"S3-509139719",
"S3-947411342",
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"S3-658478979",
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"S3-755698465",
"S3-647703887",
"S3-238278711",
"S3-217622312",
"S3-88802410",
"S3-551147530",
"S3-167873206",
"S3-465251718... |
End of preview.
Amazon ML Challenge 2026 — Business Entity Resolution archive
Team nau shunya do sau das: Rudr Pratap Singh, Uday Bhatia, Swayam Singh, Antriksh Arya.
The archive holds our code, experiment records, models and final submission for the Business Entity Resolution challenge: match Source 2/3 business records to Source 1 entities, scored by macro F0.5. The final submission's expected public score is 0.98564.
Layout
| Path | Contents |
|---|---|
final_submission/ |
nau_shunya_do_sau_das_submission.zip (package in the official structure) and FINAL_B_20260927/ (outputs, write-up, French-adaptation code, teammate assembly record) |
workspace/ |
Project workspace: source (src/, tools/), docs, reports, experiment state, dashboards, EDA, backups of earlier submissions. Credentials removed. |
models/claude_french_adapted/ |
French-adapted BGE readers. B_ftbge_v3n_normtrain is the final one (normalized training), with its training data. R3_ftbge_v3 is the raw-text variant. |
models/production/ |
Checkpoints and configs loaded by the production pipeline (mDeBERTa epoch-2, BGE control round-1, inference weights, Qwen3-Embedding retriever, policies); see MANIFEST.json |
recovered_core/ |
Recovered core of the earlier Paperspace runs (fine-tuned E5, round-5 rerankers, fullscale runs) |
cpu_host/ |
Scripts from the CPU host, key decision-model artifacts (calibration/validation cohort rows, LightGBM model, test routing features) and all 27 Sep experiment files (claude_diag_20260927/) |
extra/teammate_er4b_workspace/ |
Teammate pipeline workspace (fine-tuned multilingual-E5, Qwen3-Reranker-0.6B LoRA adapters, data, outputs, holdout audit) |
extra/models_full_fitting_mdeberta/ |
Full-fitting mDeBERTa reader checkpoint used as feature 54 (SHA prefix c6f81882) |
friend_rudr/ |
Teammate pipeline submission archive (all public-leaderboard files with candidates); home_rudr/ has the rest of the teammate's folder from the control VM (P3 package, 0.98455 final with candidates) |
vm_archive/ |
Final sweep of the three Azure VMs before deletion (29 Sep 2026): control_vm/, cpu_vm_1/, cpu_vm_2/. Each holds one .tar.gz per source folder with every file not already in this repo (code, scripts, logs, reports, metrics JSON, submitted leaderboard files, tables, chat logs, attachments), PACK_LOG.json, and NOT_UPLOADED_inventory.jsonl.gz listing the large files left behind (experiment checkpoints, score/feature arrays, storage mirrors). Credentials and private keys removed; tokens redacted. control_vm/claude_session_2aadc340_redacted.jsonl.gz is the redacted Claude session log. */large_files/ holds result files over 200 MB (earlier submissions' candidate sets, reader-training candidate lists); control_vm/extra_code/ holds C++ sources and the systemd service units. |
See FINAL_WEIGHTS.md for where each final model's weights are, final_submission/FINAL_B_20260927/Documentation_template.md for the method, and
workspace/CONTEXT_HANDOFF.md for the full project history.
The competition dataset itself is included under workspace/data/raw/; it belongs to the challenge organisers and remains subject to their terms.
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