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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.
model_size string | task string | bitwidth string | seed int64 | layer int64 | module string | out_features int64 | in_features int64 | fro_norm float64 | spectral_norm float64 | effective_rank float64 | stable_rank float64 | energy_top1 float64 | energy_top2 float64 | energy_top4 float64 | energy_top8 float64 | energy_top16 float64 | sv1 float64 | sv2 float64 | sv3 float64 | sv4 float64 | sv5 float64 | sv6 float64 | sv7 float64 | sv8 float64 | sv9 float64 | sv10 float64 | sv11 float64 | sv12 float64 | sv13 float64 | sv14 float64 | sv15 float64 | sv16 float64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1B | mnli | bf16 | 42 | 0 | k_proj | 512 | 2,048 | 0.478136 | 0.310471 | 11.830018 | 2.371702 | 0.421638 | 0.687144 | 0.843664 | 0.94075 | 1 | 0.310471 | 0.24637 | 0.154217 | 0.109544 | 0.09273 | 0.076511 | 0.063621 | 0.060785 | 0.054018 | 0.048658 | 0.047053 | 0.041414 | 0.037193 | 0.03441 | 0.032083 | 0.027093 |
1B | mnli | bf16 | 42 | 0 | o_proj | 2,048 | 2,048 | 0.888789 | 0.518331 | 13.327409 | 2.940231 | 0.340109 | 0.531859 | 0.73751 | 0.895371 | 1 | 0.518331 | 0.389194 | 0.340692 | 0.215363 | 0.204104 | 0.193881 | 0.165473 | 0.134431 | 0.120828 | 0.117049 | 0.109882 | 0.103095 | 0.09631 | 0.091316 | 0.088292 | 0.078989 |
1B | mnli | bf16 | 42 | 0 | q_proj | 2,048 | 2,048 | 1.04181 | 0.650642 | 12.65524 | 2.563854 | 0.390038 | 0.576144 | 0.81379 | 0.912971 | 1 | 0.650642 | 0.449438 | 0.423397 | 0.280477 | 0.188861 | 0.164903 | 0.15257 | 0.146661 | 0.141586 | 0.127115 | 0.112317 | 0.108451 | 0.099496 | 0.097417 | 0.090933 | 0.078859 |
1B | mnli | bf16 | 42 | 0 | v_proj | 512 | 2,048 | 0.438832 | 0.306725 | 12.108855 | 2.04692 | 0.488539 | 0.720204 | 0.825744 | 0.926386 | 1 | 0.306725 | 0.211217 | 0.112638 | 0.08739 | 0.083111 | 0.071471 | 0.061523 | 0.059836 | 0.05333 | 0.051704 | 0.045922 | 0.043571 | 0.039134 | 0.034888 | 0.033676 | 0.027728 |
1B | mnli | bf16 | 42 | 1 | k_proj | 512 | 2,048 | 0.462451 | 0.247758 | 13.453991 | 3.483966 | 0.287029 | 0.487598 | 0.732822 | 0.886742 | 1 | 0.247758 | 0.207108 | 0.162713 | 0.161146 | 0.11345 | 0.087383 | 0.08135 | 0.076111 | 0.074626 | 0.064725 | 0.059508 | 0.053684 | 0.050735 | 0.046952 | 0.044337 | 0.035996 |
1B | mnli | bf16 | 42 | 1 | o_proj | 2,048 | 2,048 | 1.010072 | 0.648706 | 12.500945 | 2.42443 | 0.412468 | 0.679533 | 0.814992 | 0.916371 | 1 | 0.648706 | 0.521989 | 0.28684 | 0.236483 | 0.190455 | 0.16604 | 0.145722 | 0.135479 | 0.125932 | 0.118509 | 0.108962 | 0.105182 | 0.095903 | 0.095057 | 0.089582 | 0.078894 |
1B | mnli | bf16 | 42 | 1 | q_proj | 2,048 | 2,048 | 1.029521 | 0.708345 | 13.281681 | 2.112425 | 0.47339 | 0.616031 | 0.741713 | 0.885521 | 1 | 0.708345 | 0.388829 | 0.273353 | 0.241846 | 0.227463 | 0.193491 | 0.181431 | 0.174151 | 0.149895 | 0.139819 | 0.136334 | 0.122884 | 0.117365 | 0.111992 | 0.099302 | 0.09724 |
1B | mnli | bf16 | 42 | 1 | v_proj | 512 | 2,048 | 0.466233 | 0.347362 | 9.977397 | 1.801536 | 0.555082 | 0.863449 | 0.918804 | 0.966002 | 1 | 0.347362 | 0.258903 | 0.083517 | 0.071116 | 0.064737 | 0.053657 | 0.040424 | 0.039442 | 0.037771 | 0.036893 | 0.03258 | 0.030578 | 0.029263 | 0.026577 | 0.02315 | 0.022525 |
1B | mnli | bf16 | 42 | 2 | k_proj | 512 | 2,048 | 0.47884 | 0.285264 | 12.966253 | 2.817647 | 0.354906 | 0.61452 | 0.763637 | 0.906944 | 1 | 0.285264 | 0.24398 | 0.139071 | 0.12186 | 0.110738 | 0.09287 | 0.079348 | 0.075331 | 0.066144 | 0.061342 | 0.055051 | 0.051231 | 0.049489 | 0.044557 | 0.040397 | 0.038431 |
1B | mnli | bf16 | 42 | 2 | o_proj | 2,048 | 2,048 | 1.018573 | 0.685337 | 11.917879 | 2.208903 | 0.452713 | 0.668478 | 0.854815 | 0.933667 | 1 | 0.685337 | 0.473132 | 0.374083 | 0.231054 | 0.170264 | 0.155564 | 0.125565 | 0.113362 | 0.112094 | 0.109873 | 0.10276 | 0.089824 | 0.088354 | 0.080834 | 0.079272 | 0.07022 |
1B | mnli | bf16 | 42 | 2 | q_proj | 2,048 | 2,048 | 1.112087 | 0.722506 | 13.550971 | 2.369163 | 0.42209 | 0.558394 | 0.731102 | 0.872195 | 1 | 0.722506 | 0.410575 | 0.36308 | 0.285951 | 0.236701 | 0.215557 | 0.196167 | 0.18309 | 0.173842 | 0.160484 | 0.151545 | 0.14106 | 0.132219 | 0.128075 | 0.114974 | 0.11008 |
1B | mnli | bf16 | 42 | 2 | v_proj | 512 | 2,048 | 0.519771 | 0.434275 | 10.186154 | 1.4325 | 0.69808 | 0.826088 | 0.911999 | 0.9659 | 1 | 0.434275 | 0.185965 | 0.117337 | 0.097169 | 0.072047 | 0.058525 | 0.056262 | 0.052733 | 0.045698 | 0.042496 | 0.039042 | 0.034444 | 0.02998 | 0.026439 | 0.023138 | 0.021779 |
1B | mnli | bf16 | 42 | 3 | k_proj | 512 | 2,048 | 0.548404 | 0.367223 | 12.154858 | 2.230191 | 0.448392 | 0.638691 | 0.818666 | 0.935618 | 1 | 0.367223 | 0.239232 | 0.191229 | 0.132509 | 0.111578 | 0.102803 | 0.082871 | 0.072714 | 0.066835 | 0.057742 | 0.053771 | 0.048162 | 0.045075 | 0.041303 | 0.036964 | 0.035307 |
1B | mnli | bf16 | 42 | 3 | o_proj | 2,048 | 2,048 | 1.056567 | 0.693695 | 13.195705 | 2.319839 | 0.431064 | 0.583719 | 0.729755 | 0.898639 | 1 | 0.693695 | 0.412812 | 0.30579 | 0.263661 | 0.253719 | 0.229345 | 0.203983 | 0.173059 | 0.150596 | 0.144825 | 0.129461 | 0.118486 | 0.113235 | 0.09997 | 0.095801 | 0.081894 |
1B | mnli | bf16 | 42 | 3 | q_proj | 2,048 | 2,048 | 1.097508 | 0.808894 | 11.898837 | 1.840907 | 0.54321 | 0.72444 | 0.846423 | 0.931755 | 1 | 0.808894 | 0.467221 | 0.312484 | 0.222003 | 0.178707 | 0.161143 | 0.154225 | 0.145242 | 0.137276 | 0.120794 | 0.106711 | 0.094917 | 0.092722 | 0.08676 | 0.080605 | 0.075819 |
1B | mnli | bf16 | 42 | 3 | v_proj | 512 | 2,048 | 0.553195 | 0.42971 | 11.33683 | 1.657314 | 0.603386 | 0.752205 | 0.866037 | 0.949342 | 1 | 0.42971 | 0.213406 | 0.152123 | 0.108137 | 0.097278 | 0.084642 | 0.067877 | 0.06526 | 0.05558 | 0.051722 | 0.047775 | 0.044584 | 0.04046 | 0.039826 | 0.034693 | 0.032273 |
1B | mnli | bf16 | 42 | 4 | k_proj | 512 | 2,048 | 0.558635 | 0.429351 | 11.548218 | 1.692899 | 0.590703 | 0.707329 | 0.852861 | 0.945331 | 1 | 0.429351 | 0.190777 | 0.175888 | 0.120333 | 0.10627 | 0.082325 | 0.075543 | 0.071275 | 0.064973 | 0.053387 | 0.051012 | 0.043525 | 0.041732 | 0.039123 | 0.036411 | 0.029906 |
1B | mnli | bf16 | 42 | 4 | o_proj | 2,048 | 2,048 | 0.949071 | 0.627225 | 12.59419 | 2.289554 | 0.436766 | 0.677989 | 0.798901 | 0.912196 | 1 | 0.627225 | 0.466131 | 0.260954 | 0.202021 | 0.181238 | 0.164037 | 0.147244 | 0.143573 | 0.134659 | 0.113866 | 0.105951 | 0.095828 | 0.090529 | 0.088441 | 0.078925 | 0.073039 |
1B | mnli | bf16 | 42 | 4 | q_proj | 2,048 | 2,048 | 1.011137 | 0.665778 | 11.717894 | 2.306542 | 0.433549 | 0.736994 | 0.854773 | 0.938482 | 1 | 0.665778 | 0.556993 | 0.283488 | 0.200129 | 0.161624 | 0.150381 | 0.142293 | 0.128839 | 0.112528 | 0.107524 | 0.099919 | 0.087753 | 0.083919 | 0.073465 | 0.069167 | 0.061354 |
1B | mnli | bf16 | 42 | 4 | v_proj | 512 | 2,048 | 0.567309 | 0.467367 | 10.109594 | 1.473411 | 0.678697 | 0.800741 | 0.919681 | 0.970007 | 1 | 0.467367 | 0.198188 | 0.164549 | 0.105846 | 0.07649 | 0.063936 | 0.057142 | 0.054709 | 0.04364 | 0.04192 | 0.034996 | 0.034515 | 0.032594 | 0.031529 | 0.027956 | 0.027152 |
1B | mnli | bf16 | 42 | 5 | k_proj | 512 | 2,048 | 0.5713 | 0.38981 | 12.526484 | 2.147938 | 0.465563 | 0.648154 | 0.804953 | 0.91968 | 1 | 0.38981 | 0.244121 | 0.181193 | 0.135447 | 0.108837 | 0.1027 | 0.089803 | 0.083591 | 0.07542 | 0.065637 | 0.060125 | 0.056149 | 0.054407 | 0.052225 | 0.047428 | 0.03891 |
1B | mnli | bf16 | 42 | 5 | o_proj | 2,048 | 2,048 | 0.946153 | 0.598205 | 12.364101 | 2.501632 | 0.399739 | 0.66548 | 0.797841 | 0.927277 | 1 | 0.598205 | 0.487743 | 0.269033 | 0.214737 | 0.2052 | 0.170707 | 0.166178 | 0.130416 | 0.118372 | 0.112606 | 0.094417 | 0.08865 | 0.087619 | 0.080318 | 0.062688 | 0.059823 |
1B | mnli | bf16 | 42 | 5 | q_proj | 2,048 | 2,048 | 1.096806 | 0.702937 | 13.71684 | 2.434594 | 0.410746 | 0.519268 | 0.697227 | 0.868716 | 1 | 0.702937 | 0.361317 | 0.340424 | 0.313357 | 0.263365 | 0.234224 | 0.214065 | 0.190403 | 0.182395 | 0.160055 | 0.153729 | 0.140076 | 0.130481 | 0.117741 | 0.116565 | 0.106382 |
1B | mnli | bf16 | 42 | 5 | v_proj | 512 | 2,048 | 0.531679 | 0.408677 | 11.367978 | 1.69254 | 0.590828 | 0.725645 | 0.86443 | 0.948808 | 1 | 0.408677 | 0.195219 | 0.163855 | 0.111281 | 0.09966 | 0.076927 | 0.069374 | 0.056477 | 0.05487 | 0.050073 | 0.045026 | 0.044163 | 0.042006 | 0.035343 | 0.034356 | 0.027955 |
1B | mnli | bf16 | 42 | 6 | k_proj | 512 | 2,048 | 0.635088 | 0.409102 | 11.374869 | 2.409926 | 0.414951 | 0.688003 | 0.875306 | 0.953229 | 1 | 0.409102 | 0.331861 | 0.207797 | 0.179908 | 0.116912 | 0.086477 | 0.073148 | 0.070225 | 0.060282 | 0.057814 | 0.052616 | 0.047489 | 0.045125 | 0.042686 | 0.040198 | 0.037286 |
1B | mnli | bf16 | 42 | 6 | o_proj | 2,048 | 2,048 | 0.869999 | 0.712906 | 11.016452 | 1.489274 | 0.671468 | 0.78134 | 0.87658 | 0.953027 | 1 | 0.712906 | 0.288378 | 0.215157 | 0.160609 | 0.147013 | 0.124875 | 0.10689 | 0.096077 | 0.084262 | 0.078318 | 0.077403 | 0.070755 | 0.060718 | 0.055294 | 0.0507 | 0.044808 |
1B | mnli | bf16 | 42 | 6 | q_proj | 2,048 | 2,048 | 1.08946 | 0.820271 | 11.177371 | 1.764044 | 0.566879 | 0.757427 | 0.887583 | 0.947052 | 1 | 0.820271 | 0.475569 | 0.340172 | 0.196897 | 0.153835 | 0.136584 | 0.120141 | 0.117607 | 0.110924 | 0.098462 | 0.097594 | 0.091962 | 0.0835 | 0.07979 | 0.074589 | 0.062948 |
1B | mnli | bf16 | 42 | 6 | v_proj | 512 | 2,048 | 0.503888 | 0.41172 | 9.940239 | 1.497835 | 0.66763 | 0.833481 | 0.913383 | 0.972579 | 1 | 0.41172 | 0.205208 | 0.115036 | 0.083987 | 0.077898 | 0.058578 | 0.057284 | 0.047427 | 0.041972 | 0.033793 | 0.03196 | 0.02846 | 0.027237 | 0.023936 | 0.022119 | 0.020572 |
1B | mnli | bf16 | 42 | 7 | k_proj | 512 | 2,048 | 1.04801 | 0.998692 | 7.278714 | 1.101207 | 0.908094 | 0.942753 | 0.969294 | 0.987982 | 1 | 0.998692 | 0.195105 | 0.138304 | 0.100116 | 0.083892 | 0.076151 | 0.065579 | 0.058205 | 0.053712 | 0.048538 | 0.044486 | 0.039111 | 0.036914 | 0.03488 | 0.031859 | 0.029259 |
1B | mnli | bf16 | 42 | 7 | o_proj | 2,048 | 2,048 | 0.852187 | 0.68204 | 10.780377 | 1.561172 | 0.640544 | 0.801935 | 0.889886 | 0.95851 | 1 | 0.68204 | 0.342353 | 0.20056 | 0.153777 | 0.134188 | 0.114995 | 0.098079 | 0.0948 | 0.077405 | 0.073809 | 0.063729 | 0.061965 | 0.057335 | 0.0544 | 0.053914 | 0.040462 |
1B | mnli | bf16 | 42 | 7 | q_proj | 2,048 | 2,048 | 1.085218 | 0.805492 | 8.912915 | 1.815143 | 0.550921 | 0.902783 | 0.94026 | 0.979879 | 1 | 0.805492 | 0.643729 | 0.164411 | 0.130787 | 0.12626 | 0.115484 | 0.100053 | 0.085852 | 0.072215 | 0.069475 | 0.058852 | 0.053905 | 0.050694 | 0.047403 | 0.037534 | 0.032558 |
1B | mnli | bf16 | 42 | 7 | v_proj | 512 | 2,048 | 0.495345 | 0.333744 | 10.930369 | 2.202882 | 0.453951 | 0.731645 | 0.890269 | 0.958566 | 1 | 0.333744 | 0.261031 | 0.174655 | 0.091743 | 0.072614 | 0.070226 | 0.058416 | 0.056044 | 0.047601 | 0.042044 | 0.040392 | 0.034476 | 0.031657 | 0.0304 | 0.029792 | 0.022338 |
1B | mnli | bf16 | 42 | 8 | k_proj | 512 | 2,048 | 0.763863 | 0.726937 | 7.296813 | 1.104176 | 0.905653 | 0.941995 | 0.968388 | 0.988556 | 1 | 0.726937 | 0.14562 | 0.095039 | 0.079795 | 0.063072 | 0.061538 | 0.048026 | 0.041192 | 0.037039 | 0.033054 | 0.03121 | 0.030706 | 0.027717 | 0.024387 | 0.022701 | 0.020433 |
1B | mnli | bf16 | 42 | 8 | o_proj | 2,048 | 2,048 | 1.008201 | 0.737695 | 9.429694 | 1.867847 | 0.535376 | 0.854277 | 0.940388 | 0.974097 | 1 | 0.737695 | 0.569345 | 0.259811 | 0.14152 | 0.105398 | 0.09866 | 0.084549 | 0.079202 | 0.074219 | 0.067826 | 0.063677 | 0.06185 | 0.054465 | 0.04744 | 0.044343 | 0.034019 |
1B | mnli | bf16 | 42 | 8 | q_proj | 2,048 | 2,048 | 0.886662 | 0.841531 | 7.279574 | 1.110134 | 0.900792 | 0.931384 | 0.967342 | 0.990206 | 1 | 0.841531 | 0.155082 | 0.128758 | 0.108122 | 0.081269 | 0.075121 | 0.056794 | 0.050014 | 0.042161 | 0.03978 | 0.033031 | 0.028439 | 0.026718 | 0.025962 | 0.024815 | 0.020893 |
1B | mnli | bf16 | 42 | 8 | v_proj | 512 | 2,048 | 0.623003 | 0.512711 | 9.295307 | 1.476503 | 0.677276 | 0.876549 | 0.93808 | 0.974893 | 1 | 0.512711 | 0.278108 | 0.125574 | 0.090074 | 0.06853 | 0.062806 | 0.055049 | 0.051156 | 0.048029 | 0.040848 | 0.039949 | 0.036681 | 0.033537 | 0.030116 | 0.020796 | 0.019074 |
1B | mnli | bf16 | 42 | 9 | k_proj | 512 | 2,048 | 0.347441 | 0.202997 | 11.880726 | 2.929451 | 0.341361 | 0.614666 | 0.842384 | 0.944391 | 1 | 0.202997 | 0.181638 | 0.139131 | 0.090176 | 0.065618 | 0.056712 | 0.052487 | 0.045132 | 0.040689 | 0.033238 | 0.032281 | 0.026855 | 0.026148 | 0.024803 | 0.02264 | 0.019437 |
1B | mnli | bf16 | 42 | 9 | o_proj | 2,048 | 2,048 | 0.615907 | 0.428267 | 11.880395 | 2.06824 | 0.483503 | 0.725299 | 0.850905 | 0.9329 | 1 | 0.428267 | 0.302858 | 0.167972 | 0.139403 | 0.099054 | 0.090527 | 0.087418 | 0.073859 | 0.072308 | 0.068674 | 0.060222 | 0.057168 | 0.05111 | 0.049852 | 0.042588 | 0.041271 |
1B | mnli | bf16 | 42 | 9 | q_proj | 2,048 | 2,048 | 0.559172 | 0.401956 | 11.497271 | 1.935235 | 0.516733 | 0.695361 | 0.865309 | 0.94889 | 1 | 0.401956 | 0.236331 | 0.184375 | 0.138362 | 0.097991 | 0.087762 | 0.069094 | 0.063679 | 0.058073 | 0.052173 | 0.048889 | 0.043848 | 0.042964 | 0.040158 | 0.033521 | 0.031483 |
1B | mnli | bf16 | 42 | 9 | v_proj | 512 | 2,048 | 0.317267 | 0.228403 | 11.542101 | 1.929498 | 0.51827 | 0.720992 | 0.863264 | 0.94528 | 1 | 0.228403 | 0.142848 | 0.095703 | 0.071846 | 0.055121 | 0.046072 | 0.040578 | 0.038053 | 0.033619 | 0.031923 | 0.029297 | 0.026754 | 0.024059 | 0.021572 | 0.020124 | 0.018316 |
1B | mnli | bf16 | 42 | 10 | k_proj | 512 | 2,048 | 0.251937 | 0.16936 | 12.65948 | 2.212912 | 0.451893 | 0.628667 | 0.778885 | 0.921223 | 1 | 0.16936 | 0.105925 | 0.075695 | 0.061684 | 0.058045 | 0.046899 | 0.044911 | 0.038062 | 0.03102 | 0.02965 | 0.026602 | 0.024812 | 0.024193 | 0.022969 | 0.020824 | 0.017 |
1B | mnli | bf16 | 42 | 10 | o_proj | 2,048 | 2,048 | 0.532705 | 0.419522 | 10.745091 | 1.612369 | 0.620205 | 0.792601 | 0.889257 | 0.957557 | 1 | 0.419522 | 0.221182 | 0.129341 | 0.103438 | 0.080643 | 0.071997 | 0.064029 | 0.059961 | 0.057801 | 0.04697 | 0.042391 | 0.039679 | 0.032309 | 0.029325 | 0.025636 | 0.023761 |
1B | mnli | bf16 | 42 | 10 | q_proj | 2,048 | 2,048 | 0.469166 | 0.287811 | 12.707808 | 2.657294 | 0.376323 | 0.571101 | 0.788389 | 0.917833 | 1 | 0.287811 | 0.20706 | 0.170847 | 0.136529 | 0.104228 | 0.086677 | 0.075659 | 0.066273 | 0.063853 | 0.058056 | 0.054053 | 0.044407 | 0.041249 | 0.039365 | 0.037397 | 0.033094 |
1B | mnli | bf16 | 42 | 10 | v_proj | 512 | 2,048 | 0.234694 | 0.154238 | 12.736726 | 2.315369 | 0.431897 | 0.638882 | 0.775958 | 0.910376 | 1 | 0.154238 | 0.106776 | 0.066251 | 0.056224 | 0.04925 | 0.045419 | 0.040473 | 0.035741 | 0.03464 | 0.029868 | 0.028373 | 0.023961 | 0.022413 | 0.019332 | 0.01779 | 0.016521 |
1B | mnli | bf16 | 42 | 11 | k_proj | 512 | 2,048 | 0.343711 | 0.252963 | 11.384301 | 1.846175 | 0.541661 | 0.688068 | 0.861171 | 0.953971 | 1 | 0.252963 | 0.131515 | 0.108864 | 0.092728 | 0.068477 | 0.055898 | 0.040936 | 0.038387 | 0.034049 | 0.031792 | 0.026207 | 0.025619 | 0.024563 | 0.023391 | 0.020236 | 0.019094 |
1B | mnli | bf16 | 42 | 11 | o_proj | 2,048 | 2,048 | 0.758357 | 0.660967 | 9.28608 | 1.316402 | 0.759646 | 0.857487 | 0.940752 | 0.976351 | 1 | 0.660967 | 0.23721 | 0.175814 | 0.130292 | 0.087102 | 0.073237 | 0.063065 | 0.059543 | 0.052908 | 0.048711 | 0.046473 | 0.044365 | 0.037314 | 0.037165 | 0.028107 | 0.027151 |
1B | mnli | bf16 | 42 | 11 | q_proj | 2,048 | 2,048 | 0.721841 | 0.564721 | 10.463219 | 1.633862 | 0.612047 | 0.749189 | 0.90626 | 0.966369 | 1 | 0.564721 | 0.267317 | 0.243025 | 0.150934 | 0.102369 | 0.096573 | 0.084086 | 0.066661 | 0.06576 | 0.056361 | 0.049555 | 0.046317 | 0.040252 | 0.037801 | 0.035526 | 0.033327 |
1B | mnli | bf16 | 42 | 11 | v_proj | 512 | 2,048 | 0.295228 | 0.212376 | 11.31363 | 1.932425 | 0.517485 | 0.756786 | 0.86479 | 0.945465 | 1 | 0.212376 | 0.144421 | 0.079624 | 0.05544 | 0.053 | 0.039992 | 0.038215 | 0.034102 | 0.032414 | 0.03127 | 0.027842 | 0.025072 | 0.022173 | 0.020023 | 0.015417 | 0.01381 |
1B | mnli | bf16 | 42 | 12 | k_proj | 512 | 2,048 | 0.236703 | 0.142567 | 12.759238 | 2.756586 | 0.362768 | 0.552197 | 0.778223 | 0.919345 | 1 | 0.142567 | 0.103021 | 0.089815 | 0.067801 | 0.054548 | 0.045545 | 0.042244 | 0.032749 | 0.030108 | 0.027765 | 0.026177 | 0.025462 | 0.022475 | 0.021851 | 0.016821 | 0.015572 |
1B | mnli | bf16 | 42 | 12 | o_proj | 2,048 | 2,048 | 0.564006 | 0.391309 | 11.207813 | 2.077443 | 0.481361 | 0.693089 | 0.878428 | 0.954671 | 1 | 0.391309 | 0.259521 | 0.201867 | 0.134933 | 0.096393 | 0.076434 | 0.070824 | 0.064059 | 0.057935 | 0.051568 | 0.048706 | 0.042009 | 0.038634 | 0.031774 | 0.030955 | 0.028392 |
1B | mnli | bf16 | 42 | 12 | q_proj | 2,048 | 2,048 | 0.505664 | 0.316187 | 12.648951 | 2.55762 | 0.390989 | 0.608284 | 0.799578 | 0.916154 | 1 | 0.316187 | 0.235715 | 0.164074 | 0.1483 | 0.10396 | 0.08825 | 0.077449 | 0.072208 | 0.069816 | 0.063352 | 0.057845 | 0.047867 | 0.045617 | 0.043502 | 0.040944 | 0.035559 |
1B | mnli | bf16 | 42 | 12 | v_proj | 512 | 2,048 | 0.251046 | 0.146815 | 12.380927 | 2.923918 | 0.342007 | 0.601934 | 0.812929 | 0.930041 | 1 | 0.146815 | 0.127991 | 0.086498 | 0.076262 | 0.053574 | 0.04239 | 0.039948 | 0.033436 | 0.030712 | 0.026811 | 0.026379 | 0.025334 | 0.022202 | 0.01843 | 0.017853 | 0.016065 |
1B | mnli | bf16 | 42 | 13 | k_proj | 512 | 2,048 | 0.290231 | 0.221816 | 11.640681 | 1.711984 | 0.584118 | 0.6997 | 0.84115 | 0.94511 | 1 | 0.221816 | 0.098671 | 0.08858 | 0.063784 | 0.052994 | 0.052513 | 0.044252 | 0.035109 | 0.033347 | 0.027629 | 0.026602 | 0.024831 | 0.022884 | 0.019326 | 0.016571 | 0.015881 |
1B | mnli | bf16 | 42 | 13 | o_proj | 2,048 | 2,048 | 0.504243 | 0.372986 | 10.672233 | 1.827663 | 0.547147 | 0.71599 | 0.89736 | 0.964727 | 1 | 0.372986 | 0.207196 | 0.165898 | 0.136357 | 0.080438 | 0.072818 | 0.053532 | 0.049902 | 0.044434 | 0.044018 | 0.037745 | 0.033509 | 0.02882 | 0.026223 | 0.025804 | 0.018032 |
1B | mnli | bf16 | 42 | 13 | q_proj | 2,048 | 2,048 | 0.727863 | 0.635318 | 9.717136 | 1.312559 | 0.761871 | 0.856533 | 0.923107 | 0.97062 | 1 | 0.635318 | 0.223943 | 0.146701 | 0.117257 | 0.100089 | 0.079368 | 0.070122 | 0.062747 | 0.059363 | 0.052503 | 0.0499 | 0.044848 | 0.040276 | 0.035319 | 0.033248 | 0.028428 |
1B | mnli | bf16 | 42 | 13 | v_proj | 512 | 2,048 | 0.271593 | 0.204115 | 10.99699 | 1.77047 | 0.564822 | 0.748861 | 0.889345 | 0.951293 | 1 | 0.204115 | 0.116513 | 0.089564 | 0.048383 | 0.038427 | 0.033748 | 0.032756 | 0.029681 | 0.028585 | 0.026846 | 0.022953 | 0.021445 | 0.020514 | 0.015731 | 0.014606 | 0.01366 |
1B | mnli | bf16 | 42 | 14 | k_proj | 512 | 2,048 | 0.310103 | 0.259472 | 10.970112 | 1.428342 | 0.700112 | 0.780424 | 0.875915 | 0.952726 | 1 | 0.259472 | 0.087881 | 0.078791 | 0.05454 | 0.048988 | 0.044002 | 0.041121 | 0.036871 | 0.031049 | 0.029336 | 0.025608 | 0.024801 | 0.023219 | 0.019981 | 0.01802 | 0.013693 |
1B | mnli | bf16 | 42 | 14 | o_proj | 2,048 | 2,048 | 0.454395 | 0.3248 | 10.217476 | 1.957203 | 0.510933 | 0.773872 | 0.903141 | 0.973245 | 1 | 0.3248 | 0.233003 | 0.12722 | 0.102498 | 0.073805 | 0.064927 | 0.052231 | 0.045651 | 0.036586 | 0.034414 | 0.028683 | 0.025559 | 0.023939 | 0.021599 | 0.01675 | 0.014327 |
1B | mnli | bf16 | 42 | 14 | q_proj | 2,048 | 2,048 | 0.789338 | 0.712999 | 8.305222 | 1.225603 | 0.815925 | 0.888052 | 0.949678 | 0.985385 | 1 | 0.712999 | 0.211989 | 0.165914 | 0.104255 | 0.092332 | 0.079928 | 0.061761 | 0.059326 | 0.047368 | 0.045091 | 0.041869 | 0.032756 | 0.030851 | 0.023574 | 0.016608 | 0.014821 |
1B | mnli | bf16 | 42 | 14 | v_proj | 512 | 2,048 | 0.290734 | 0.233817 | 9.906421 | 1.546115 | 0.646782 | 0.818126 | 0.913666 | 0.973152 | 1 | 0.233817 | 0.120346 | 0.072204 | 0.053501 | 0.045631 | 0.038684 | 0.02875 | 0.024959 | 0.022746 | 0.021335 | 0.019603 | 0.017799 | 0.013655 | 0.013064 | 0.012033 | 0.009684 |
1B | mnli | bf16 | 42 | 15 | k_proj | 512 | 2,048 | 0.284576 | 0.219658 | 11.308485 | 1.678431 | 0.595795 | 0.730932 | 0.8733 | 0.94992 | 1 | 0.219658 | 0.104613 | 0.086184 | 0.064045 | 0.044361 | 0.043067 | 0.036185 | 0.032755 | 0.030047 | 0.026861 | 0.02439 | 0.022192 | 0.021245 | 0.019216 | 0.01695 | 0.015365 |
1B | mnli | bf16 | 42 | 15 | o_proj | 2,048 | 2,048 | 0.799081 | 0.748817 | 6.738235 | 1.138757 | 0.87815 | 0.939442 | 0.9742 | 0.993698 | 1 | 0.748817 | 0.19783 | 0.113401 | 0.096615 | 0.075455 | 0.055704 | 0.046589 | 0.038517 | 0.03296 | 0.030184 | 0.026896 | 0.020458 | 0.018591 | 0.016187 | 0.012773 | 0.010662 |
1B | mnli | bf16 | 42 | 15 | q_proj | 2,048 | 2,048 | 0.402176 | 0.368378 | 8.810912 | 1.19191 | 0.83899 | 0.886415 | 0.945224 | 0.978253 | 1 | 0.368378 | 0.087583 | 0.076828 | 0.060079 | 0.045591 | 0.036854 | 0.032329 | 0.029333 | 0.027583 | 0.025924 | 0.024192 | 0.022154 | 0.018923 | 0.01645 | 0.014568 | 0.012948 |
1B | mnli | bf16 | 42 | 15 | v_proj | 512 | 2,048 | 0.219354 | 0.157181 | 11.361529 | 1.947566 | 0.513461 | 0.726961 | 0.867169 | 0.948218 | 1 | 0.157181 | 0.101355 | 0.064891 | 0.050352 | 0.035813 | 0.034828 | 0.027163 | 0.025814 | 0.024301 | 0.020962 | 0.019853 | 0.019549 | 0.016542 | 0.012957 | 0.011583 | 0.010467 |
1B | mnli | bf16 | 43 | 0 | k_proj | 512 | 2,048 | 0.525034 | 0.370646 | 11.838099 | 2.006572 | 0.498362 | 0.67992 | 0.835457 | 0.943989 | 1 | 0.370646 | 0.223715 | 0.166136 | 0.123589 | 0.108974 | 0.087715 | 0.075267 | 0.068435 | 0.058817 | 0.048866 | 0.047497 | 0.043904 | 0.041712 | 0.039392 | 0.033876 | 0.031145 |
1B | mnli | bf16 | 43 | 0 | o_proj | 2,048 | 2,048 | 0.943528 | 0.658422 | 12.204793 | 2.053527 | 0.486967 | 0.68301 | 0.82109 | 0.928414 | 1 | 0.658422 | 0.417764 | 0.284822 | 0.204453 | 0.186299 | 0.155885 | 0.146549 | 0.122721 | 0.113369 | 0.105714 | 0.09965 | 0.086728 | 0.084156 | 0.08012 | 0.072155 | 0.059514 |
1B | mnli | bf16 | 43 | 0 | q_proj | 2,048 | 2,048 | 0.994196 | 0.632905 | 13.048338 | 2.46756 | 0.405259 | 0.579734 | 0.765672 | 0.89896 | 1 | 0.632905 | 0.415279 | 0.349407 | 0.248396 | 0.212656 | 0.177659 | 0.169132 | 0.162342 | 0.146966 | 0.139974 | 0.120029 | 0.108944 | 0.102871 | 0.092377 | 0.087608 | 0.074916 |
1B | mnli | bf16 | 43 | 0 | v_proj | 512 | 2,048 | 0.431672 | 0.242943 | 11.87098 | 3.157168 | 0.31674 | 0.623846 | 0.845368 | 0.94255 | 1 | 0.242943 | 0.23922 | 0.169015 | 0.112749 | 0.0854 | 0.071746 | 0.05798 | 0.048028 | 0.047143 | 0.043307 | 0.041434 | 0.036768 | 0.032262 | 0.031212 | 0.029632 | 0.025407 |
1B | mnli | bf16 | 43 | 1 | k_proj | 512 | 2,048 | 0.449253 | 0.25412 | 13.737665 | 3.12541 | 0.319958 | 0.497645 | 0.692892 | 0.868256 | 1 | 0.25412 | 0.189374 | 0.155156 | 0.123827 | 0.103013 | 0.09699 | 0.09045 | 0.084815 | 0.077145 | 0.075058 | 0.063566 | 0.054471 | 0.049813 | 0.045085 | 0.044574 | 0.038681 |
1B | mnli | bf16 | 43 | 1 | o_proj | 2,048 | 2,048 | 1.008146 | 0.652155 | 12.796964 | 2.389712 | 0.41846 | 0.665858 | 0.794603 | 0.900546 | 1 | 0.652155 | 0.501443 | 0.281978 | 0.226582 | 0.185709 | 0.164256 | 0.158472 | 0.14524 | 0.143934 | 0.129443 | 0.121673 | 0.118342 | 0.100394 | 0.094924 | 0.089891 | 0.087346 |
1B | mnli | bf16 | 43 | 1 | q_proj | 2,048 | 2,048 | 0.977634 | 0.565689 | 14.285599 | 2.986736 | 0.334814 | 0.467776 | 0.63732 | 0.834866 | 1 | 0.565689 | 0.356484 | 0.297139 | 0.271576 | 0.248358 | 0.232348 | 0.193218 | 0.18923 | 0.162297 | 0.157286 | 0.15436 | 0.14506 | 0.140112 | 0.126702 | 0.118134 | 0.110637 |
1B | mnli | bf16 | 43 | 1 | v_proj | 512 | 2,048 | 0.476923 | 0.384321 | 10.870882 | 1.539957 | 0.649369 | 0.786611 | 0.88587 | 0.956101 | 1 | 0.384321 | 0.176682 | 0.111868 | 0.100313 | 0.078683 | 0.065892 | 0.055429 | 0.048675 | 0.044899 | 0.043509 | 0.039251 | 0.036966 | 0.034128 | 0.028409 | 0.026257 | 0.022533 |
1B | mnli | bf16 | 43 | 2 | k_proj | 512 | 2,048 | 0.478025 | 0.350643 | 12.682701 | 1.858539 | 0.538057 | 0.655171 | 0.788146 | 0.910546 | 1 | 0.350643 | 0.16359 | 0.132476 | 0.113295 | 0.103334 | 0.082092 | 0.078133 | 0.06669 | 0.062809 | 0.060583 | 0.050202 | 0.049794 | 0.048247 | 0.046602 | 0.042732 | 0.038734 |
1B | mnli | bf16 | 43 | 2 | o_proj | 2,048 | 2,048 | 0.910749 | 0.545678 | 12.884722 | 2.785638 | 0.358984 | 0.609002 | 0.779764 | 0.907327 | 1 | 0.545678 | 0.45539 | 0.30587 | 0.219284 | 0.204501 | 0.16248 | 0.137749 | 0.136429 | 0.122452 | 0.113439 | 0.109312 | 0.09684 | 0.094086 | 0.084967 | 0.077965 | 0.074356 |
1B | mnli | bf16 | 43 | 2 | q_proj | 2,048 | 2,048 | 1.063551 | 0.620186 | 13.151608 | 2.940853 | 0.340037 | 0.635758 | 0.77097 | 0.888032 | 1 | 0.620186 | 0.578362 | 0.304282 | 0.245676 | 0.203927 | 0.180129 | 0.171998 | 0.169699 | 0.151783 | 0.141086 | 0.131574 | 0.130226 | 0.120156 | 0.11725 | 0.111792 | 0.093568 |
1B | mnli | bf16 | 43 | 2 | v_proj | 512 | 2,048 | 0.48345 | 0.342049 | 11.529667 | 1.997673 | 0.500582 | 0.666989 | 0.875654 | 0.9442 | 1 | 0.342049 | 0.197213 | 0.191818 | 0.109434 | 0.071897 | 0.070558 | 0.055212 | 0.053148 | 0.047822 | 0.046923 | 0.045622 | 0.040222 | 0.038269 | 0.035323 | 0.03382 | 0.031588 |
1B | mnli | bf16 | 43 | 3 | k_proj | 512 | 2,048 | 0.608124 | 0.421878 | 11.715813 | 2.077829 | 0.481272 | 0.734368 | 0.855108 | 0.939286 | 1 | 0.421878 | 0.305939 | 0.165206 | 0.13175 | 0.110713 | 0.085326 | 0.078373 | 0.073824 | 0.069074 | 0.061431 | 0.054808 | 0.053339 | 0.049313 | 0.047191 | 0.042016 | 0.040435 |
1B | mnli | bf16 | 43 | 3 | o_proj | 2,048 | 2,048 | 1.098714 | 0.845931 | 11.655677 | 1.686943 | 0.592788 | 0.702811 | 0.845333 | 0.945415 | 1 | 0.845931 | 0.364439 | 0.307449 | 0.278433 | 0.222759 | 0.173372 | 0.154078 | 0.131897 | 0.112924 | 0.108157 | 0.099367 | 0.09755 | 0.082281 | 0.078287 | 0.070054 | 0.065173 |
1B | mnli | bf16 | 43 | 3 | q_proj | 2,048 | 2,048 | 1.082156 | 0.705556 | 12.761952 | 2.352432 | 0.425092 | 0.62019 | 0.797359 | 0.911831 | 1 | 0.705556 | 0.477987 | 0.356695 | 0.283275 | 0.222395 | 0.178708 | 0.162818 | 0.1617 | 0.142246 | 0.129233 | 0.117196 | 0.114576 | 0.10631 | 0.105145 | 0.096177 | 0.088582 |
1B | mnli | bf16 | 43 | 3 | v_proj | 512 | 2,048 | 0.522757 | 0.397189 | 11.18111 | 1.732228 | 0.577291 | 0.736952 | 0.881299 | 0.948763 | 1 | 0.397189 | 0.208881 | 0.180697 | 0.082434 | 0.080392 | 0.071025 | 0.061439 | 0.05616 | 0.052088 | 0.047109 | 0.045836 | 0.042241 | 0.040387 | 0.038479 | 0.033087 | 0.031268 |
1B | mnli | bf16 | 43 | 4 | k_proj | 512 | 2,048 | 0.622087 | 0.5203 | 10.427949 | 1.429536 | 0.699528 | 0.813285 | 0.895916 | 0.963723 | 1 | 0.5203 | 0.209817 | 0.142252 | 0.10836 | 0.099189 | 0.085829 | 0.069323 | 0.065039 | 0.05724 | 0.050046 | 0.04721 | 0.041294 | 0.038711 | 0.035811 | 0.029612 | 0.025812 |
1B | mnli | bf16 | 43 | 4 | o_proj | 2,048 | 2,048 | 0.955416 | 0.578482 | 13.185519 | 2.727755 | 0.366602 | 0.598651 | 0.745534 | 0.896828 | 1 | 0.578482 | 0.460238 | 0.265994 | 0.251645 | 0.224422 | 0.19181 | 0.165306 | 0.153694 | 0.140029 | 0.12455 | 0.119644 | 0.106274 | 0.10115 | 0.094367 | 0.092177 | 0.076253 |
1B | mnli | bf16 | 43 | 4 | q_proj | 2,048 | 2,048 | 1.017293 | 0.740741 | 11.820342 | 1.886073 | 0.530202 | 0.764178 | 0.841404 | 0.932601 | 1 | 0.740741 | 0.492075 | 0.204849 | 0.194826 | 0.174228 | 0.155859 | 0.144173 | 0.137641 | 0.116614 | 0.112354 | 0.098619 | 0.093042 | 0.08665 | 0.08457 | 0.078176 | 0.066129 |
1B | mnli | bf16 | 43 | 4 | v_proj | 512 | 2,048 | 0.538822 | 0.420563 | 10.979108 | 1.641455 | 0.609216 | 0.749738 | 0.880811 | 0.956532 | 1 | 0.420563 | 0.201984 | 0.156316 | 0.116704 | 0.082721 | 0.078753 | 0.070849 | 0.062607 | 0.05583 | 0.051629 | 0.044549 | 0.038914 | 0.031677 | 0.030729 | 0.027907 | 0.024737 |
1B | mnli | bf16 | 43 | 5 | k_proj | 512 | 2,048 | 0.56062 | 0.398466 | 13.024425 | 1.979496 | 0.505179 | 0.627365 | 0.752831 | 0.891044 | 1 | 0.398466 | 0.195966 | 0.155125 | 0.123975 | 0.112974 | 0.111042 | 0.099428 | 0.09198 | 0.08701 | 0.077111 | 0.071726 | 0.070252 | 0.061826 | 0.057666 | 0.045032 | 0.038363 |
1B | mnli | bf16 | 43 | 5 | o_proj | 2,048 | 2,048 | 0.914655 | 0.581399 | 12.151553 | 2.474941 | 0.40405 | 0.672142 | 0.823298 | 0.929573 | 1 | 0.581399 | 0.473586 | 0.283622 | 0.214511 | 0.180519 | 0.148774 | 0.134902 | 0.126448 | 0.112603 | 0.104994 | 0.099744 | 0.089321 | 0.081146 | 0.066422 | 0.062051 | 0.049412 |
1B | mnli | bf16 | 43 | 5 | q_proj | 2,048 | 2,048 | 1.092491 | 0.730368 | 13.265662 | 2.237444 | 0.446939 | 0.559279 | 0.738447 | 0.89297 | 1 | 0.730368 | 0.366172 | 0.354402 | 0.297056 | 0.252561 | 0.218232 | 0.203426 | 0.177862 | 0.154723 | 0.152961 | 0.14216 | 0.125363 | 0.120152 | 0.10943 | 0.098715 | 0.091248 |
1B | mnli | bf16 | 43 | 5 | v_proj | 512 | 2,048 | 0.49224 | 0.397978 | 11.339079 | 1.529797 | 0.653681 | 0.767925 | 0.860616 | 0.947654 | 1 | 0.397978 | 0.166376 | 0.108174 | 0.103718 | 0.081643 | 0.081016 | 0.067017 | 0.058043 | 0.053306 | 0.046295 | 0.043028 | 0.038704 | 0.036353 | 0.035219 | 0.031854 | 0.027795 |
1B | mnli | bf16 | 43 | 6 | k_proj | 512 | 2,048 | 0.729459 | 0.484688 | 10.970994 | 2.265043 | 0.441493 | 0.682403 | 0.883912 | 0.959452 | 1 | 0.484688 | 0.358038 | 0.27889 | 0.171597 | 0.12078 | 0.109916 | 0.086655 | 0.077571 | 0.072831 | 0.067112 | 0.057262 | 0.050587 | 0.04983 | 0.039206 | 0.033078 | 0.028553 |
1B | mnli | bf16 | 43 | 6 | o_proj | 2,048 | 2,048 | 0.881184 | 0.642235 | 12.361602 | 1.882543 | 0.531196 | 0.688941 | 0.811179 | 0.920016 | 1 | 0.642235 | 0.349981 | 0.228664 | 0.206467 | 0.169631 | 0.145621 | 0.134981 | 0.127709 | 0.119617 | 0.105922 | 0.092129 | 0.087607 | 0.080593 | 0.074406 | 0.0665 | 0.062948 |
1B | mnli | bf16 | 43 | 6 | q_proj | 2,048 | 2,048 | 1.112751 | 0.857365 | 11.237574 | 1.68448 | 0.593655 | 0.764686 | 0.883656 | 0.947443 | 1 | 0.857365 | 0.460188 | 0.300681 | 0.238542 | 0.153305 | 0.152016 | 0.137839 | 0.115639 | 0.114335 | 0.103169 | 0.099193 | 0.089848 | 0.084903 | 0.080297 | 0.074617 | 0.064994 |
1B | mnli | bf16 | 43 | 6 | v_proj | 512 | 2,048 | 0.526819 | 0.419101 | 10.412677 | 1.580106 | 0.632869 | 0.813559 | 0.908433 | 0.963203 | 1 | 0.419101 | 0.223939 | 0.12961 | 0.097634 | 0.073962 | 0.064341 | 0.056992 | 0.048399 | 0.047108 | 0.042297 | 0.038593 | 0.036235 | 0.033458 | 0.030485 | 0.028471 | 0.023296 |
1B | mnli | bf16 | 43 | 7 | k_proj | 512 | 2,048 | 0.821196 | 0.745361 | 8.591827 | 1.213838 | 0.823833 | 0.898825 | 0.950014 | 0.980809 | 1 | 0.745361 | 0.224882 | 0.159957 | 0.094516 | 0.085838 | 0.075771 | 0.066904 | 0.056409 | 0.05383 | 0.048078 | 0.045836 | 0.041025 | 0.037665 | 0.03161 | 0.029859 | 0.025277 |
1B | mnli | bf16 | 43 | 7 | o_proj | 2,048 | 2,048 | 0.758662 | 0.514481 | 12.112744 | 2.174486 | 0.459879 | 0.667431 | 0.826834 | 0.931628 | 1 | 0.514481 | 0.34563 | 0.262455 | 0.151211 | 0.143416 | 0.124755 | 0.118567 | 0.100626 | 0.087378 | 0.082617 | 0.078366 | 0.074355 | 0.066464 | 0.064451 | 0.051378 | 0.044849 |
1B | mnli | bf16 | 43 | 7 | q_proj | 2,048 | 2,048 | 1.309998 | 1.268944 | 6.397517 | 1.065751 | 0.938306 | 0.960962 | 0.978865 | 0.990928 | 1 | 1.268944 | 0.197183 | 0.150119 | 0.090482 | 0.083293 | 0.076385 | 0.067426 | 0.058156 | 0.054542 | 0.053132 | 0.047865 | 0.043861 | 0.042833 | 0.04096 | 0.033785 | 0.030029 |
1B | mnli | bf16 | 43 | 7 | v_proj | 512 | 2,048 | 0.539899 | 0.385385 | 10.626718 | 1.96261 | 0.509526 | 0.751293 | 0.901781 | 0.964491 | 1 | 0.385385 | 0.265468 | 0.185023 | 0.098143 | 0.077701 | 0.074044 | 0.067928 | 0.046318 | 0.045439 | 0.039993 | 0.039253 | 0.034723 | 0.034172 | 0.033136 | 0.029532 | 0.02832 |
1B | mnli | bf16 | 43 | 8 | k_proj | 512 | 2,048 | 0.997032 | 0.962142 | 5.945685 | 1.073844 | 0.931234 | 0.958187 | 0.98553 | 0.994666 | 1 | 0.962142 | 0.163689 | 0.13818 | 0.089928 | 0.054602 | 0.049132 | 0.044124 | 0.041704 | 0.034666 | 0.030715 | 0.027756 | 0.024307 | 0.023304 | 0.022579 | 0.01941 | 0.019149 |
1B | mnli | bf16 | 43 | 8 | o_proj | 2,048 | 2,048 | 1.006823 | 0.777847 | 9.948487 | 1.675399 | 0.596873 | 0.840463 | 0.923957 | 0.96838 | 1 | 0.777847 | 0.496916 | 0.257452 | 0.135485 | 0.122866 | 0.112806 | 0.097342 | 0.087948 | 0.081386 | 0.073042 | 0.065018 | 0.063068 | 0.060906 | 0.059866 | 0.049645 | 0.04616 |
1B | mnli | bf16 | 43 | 8 | q_proj | 2,048 | 2,048 | 0.979087 | 0.916909 | 7.438919 | 1.140224 | 0.877021 | 0.918164 | 0.967768 | 0.988773 | 1 | 0.916909 | 0.198597 | 0.186208 | 0.113477 | 0.086065 | 0.076523 | 0.059666 | 0.057555 | 0.052286 | 0.049258 | 0.041794 | 0.03775 | 0.032006 | 0.023243 | 0.021301 | 0.020306 |
1B | mnli | bf16 | 43 | 8 | v_proj | 512 | 2,048 | 0.616029 | 0.473115 | 8.565449 | 1.69538 | 0.589838 | 0.915004 | 0.952688 | 0.981988 | 1 | 0.473115 | 0.35128 | 0.093542 | 0.074503 | 0.066404 | 0.053393 | 0.046801 | 0.040848 | 0.036754 | 0.034593 | 0.031192 | 0.029634 | 0.029135 | 0.025307 | 0.023049 | 0.020402 |
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 questionsaggregate_results.csv— per-run metricsaggregate_results_by_task.csv,aggregate_results_by_condition.csvadapter_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 sizesplots/— 7 figures
Adapters live in Jeesup/llama32-<size>-<task>-<bitwidth>-lora-seed<seed>.
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