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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 19 new columns ({'test_majority_baseline', 'test_accuracy', 'n_classes', 'run_name', 'train_runtime_sec', 'lora_init_source', 'train_steps', 'val_macro_f1', 'val_loss', 'train_loss', 'trainable_params', 'gpu', 'test_loss', 'throughput_tokens_per_sec', 'val_accuracy', 'peak_gpu_mem_reserved_gib', 'throughput_samples_per_sec', 'test_macro_f1', 'peak_gpu_mem_gib'}) and 29 missing columns ({'sv1', 'sv2', 'sv8', 'energy_top2', 'fro_norm', 'sv5', 'energy_top1', 'stable_rank', 'energy_top16', 'layer', 'sv15', 'sv16', 'sv9', 'module', 'sv7', 'in_features', 'sv10', 'out_features', 'energy_top4', 'sv12', 'energy_top8', 'sv13', 'sv3', 'spectral_norm', 'sv4', 'sv14', 'effective_rank', 'sv11', 'sv6'}).

This happened while the csv dataset builder was generating data using

hf://datasets/Jeesup/glue-lora-bitwidth-results/aggregate_results.csv (at revision 66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d), ['hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/adapter_layer_metrics.csv', 'hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/aggregate_results.csv', 'hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/aggregate_results_by_condition.csv', 'hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/aggregate_results_by_task.csv', 'hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/gamma_table.csv', 'hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/pairwise_geometry_metrics.csv', 'hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/swap_penalty.csv', 'hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/swap_penalty_by_task.csv', 'hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/swap_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
              run_name: string
              model_size: string
              task: string
              bitwidth: string
              seed: int64
              n_classes: int64
              val_accuracy: double
              val_macro_f1: double
              val_loss: double
              test_accuracy: double
              test_macro_f1: double
              test_loss: double
              test_majority_baseline: double
              train_loss: double
              train_steps: int64
              train_runtime_sec: double
              throughput_samples_per_sec: double
              throughput_tokens_per_sec: double
              peak_gpu_mem_gib: double
              peak_gpu_mem_reserved_gib: double
              trainable_params: int64
              gpu: string
              lora_init_source: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 3173
              to
              {'model_size': Value('string'), 'task': Value('string'), 'bitwidth': Value('string'), 'seed': Value('int64'), 'layer': Value('int64'), 'module': Value('string'), 'out_features': Value('int64'), 'in_features': Value('int64'), 'fro_norm': Value('float64'), 'spectral_norm': Value('float64'), 'effective_rank': Value('float64'), 'stable_rank': Value('float64'), 'energy_top1': Value('float64'), 'energy_top2': Value('float64'), 'energy_top4': Value('float64'), 'energy_top8': Value('float64'), 'energy_top16': Value('float64'), 'sv1': Value('float64'), 'sv2': Value('float64'), 'sv3': Value('float64'), 'sv4': Value('float64'), 'sv5': Value('float64'), 'sv6': Value('float64'), 'sv7': Value('float64'), 'sv8': Value('float64'), 'sv9': Value('float64'), 'sv10': Value('float64'), 'sv11': Value('float64'), 'sv12': Value('float64'), 'sv13': Value('float64'), 'sv14': Value('float64'), 'sv15': Value('float64'), 'sv16': Value('float64')}
              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 19 new columns ({'test_majority_baseline', 'test_accuracy', 'n_classes', 'run_name', 'train_runtime_sec', 'lora_init_source', 'train_steps', 'val_macro_f1', 'val_loss', 'train_loss', 'trainable_params', 'gpu', 'test_loss', 'throughput_tokens_per_sec', 'val_accuracy', 'peak_gpu_mem_reserved_gib', 'throughput_samples_per_sec', 'test_macro_f1', 'peak_gpu_mem_gib'}) and 29 missing columns ({'sv1', 'sv2', 'sv8', 'energy_top2', 'fro_norm', 'sv5', 'energy_top1', 'stable_rank', 'energy_top16', 'layer', 'sv15', 'sv16', 'sv9', 'module', 'sv7', 'in_features', 'sv10', 'out_features', 'energy_top4', 'sv12', 'energy_top8', 'sv13', 'sv3', 'spectral_norm', 'sv4', 'sv14', 'effective_rank', 'sv11', 'sv6'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/Jeesup/glue-lora-bitwidth-results/aggregate_results.csv (at revision 66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d), ['hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/adapter_layer_metrics.csv', 'hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/aggregate_results.csv', 'hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/aggregate_results_by_condition.csv', 'hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/aggregate_results_by_task.csv', 'hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/gamma_table.csv', 'hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/pairwise_geometry_metrics.csv', 'hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/swap_penalty.csv', 'hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/swap_penalty_by_task.csv', 'hf://datasets/Jeesup/glue-lora-bitwidth-results@66d10c988fbfb6a2d94131cfc19c5ca381ad6c0d/swap_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)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

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out_features
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in_features
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fro_norm
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spectral_norm
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effective_rank
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stable_rank
float64
energy_top1
float64
energy_top2
float64
energy_top4
float64
energy_top8
float64
energy_top16
float64
sv1
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sv2
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sv3
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sv4
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sv5
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sv6
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sv7
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sv8
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sv9
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End of preview.

GLUE LoRA x Backbone Bit-Width — combined results

Aggregated metrics, LoRA geometry analysis and figures for a controlled study of whether backbone bit-width (bf16 / int8 / nf4) changes what a LoRA adapter learns.

Grid: 2 model sizes (1B, 3B) x 4 GLUE tasks (MNLI, QQP, SST-2, RTE) x 3 bit-widths x 3 seeds = 72 runs (0 present here).

For each (model size, seed) the adapter initialisation is identical across bit-widths, so cross-bit differences are attributable to the backbone. The headline statistic is

Gamma = mean cross-bit-width adapter distance / mean within-bit-width seed distance

Gamma > 1 means bit-width perturbs the adapter more than the random seed does.

Files

  • results_summary.md — the report, answering the 8 study questions
  • aggregate_results.csv — per-run metrics
  • aggregate_results_by_task.csv, aggregate_results_by_condition.csv
  • adapter_layer_metrics.csv — per-adapter per-layer geometry (norms, effective rank, stable rank, singular values, energy)
  • pairwise_geometry_metrics.csv — per-pair per-layer comparisons (Frobenius distance, cosine, principal angles, projection overlap, sign agreement)
  • gamma_table.csv — bit-width vs seed effect sizes
  • plots/ — 7 figures

Adapters live in Jeesup/llama32-<size>-<task>-<bitwidth>-lora-seed<seed>.

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