Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code: DatasetGenerationError
Exception: ArrowNotImplementedError
Message: Cannot write struct type 'task_hashes' with no child field to Parquet. Consider adding a dummy child field.
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 620, in write_table
self._build_writer(inferred_schema=pa_table.schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 441, in _build_writer
self.pa_writer = self._WRITER_CLASS(self.stream, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
self.writer = _parquet.ParquetWriter(
File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'task_hashes' with no child field to Parquet. Consider adding a dummy child field.
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 1886, in _prepare_split_single
num_examples, num_bytes = writer.finalize()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 639, in finalize
self._build_writer(self.schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 441, in _build_writer
self.pa_writer = self._WRITER_CLASS(self.stream, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
self.writer = _parquet.ParquetWriter(
File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'task_hashes' with no child field to Parquet. Consider adding a dummy child field.
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 1438, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1050, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, 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 1897, 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.
results
dict | groups
dict | group_subtasks
dict | configs
dict | versions
dict | n-shot
dict | n-samples
dict | config
dict | git_hash
string | date
float64 | pretty_env_info
string | transformers_version
string | upper_git_hash
null | task_hashes
dict | model_source
string | model_name
string | model_name_sanitized
string | start_time
float64 | end_time
float64 | total_evaluation_time_seconds
string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
{
"blimp": {
"acc,none": 0.5102835820895523,
"acc_stderr,none": 0.0018749288807151285,
"alias": "blimp"
},
"blimp_adjunct_island": {
"acc,none": 0.596,
"acc_stderr,none": 0.015524980677122437,
"alias": " - blimp_adjunct_island"
},
"blimp_anaphor_gender_agreement": {
"acc,none": 0.69,
"acc_stderr,none": 0.014632638658632766,
"alias": " - blimp_anaphor_gender_agreement"
},
"blimp_anaphor_number_agreement": {
"acc,none": 0.613,
"acc_stderr,none": 0.015410011955494015,
"alias": " - blimp_anaphor_number_agreement"
},
"blimp_animate_subject_passive": {
"acc,none": 0.567,
"acc_stderr,none": 0.01567663091218125,
"alias": " - blimp_animate_subject_passive"
},
"blimp_animate_subject_trans": {
"acc,none": 0.784,
"acc_stderr,none": 0.013019735539307761,
"alias": " - blimp_animate_subject_trans"
},
"blimp_causative": {
"acc,none": 0.394,
"acc_stderr,none": 0.015459721957493382,
"alias": " - blimp_causative"
},
"blimp_complex_NP_island": {
"acc,none": 0.497,
"acc_stderr,none": 0.01581901517924682,
"alias": " - blimp_complex_NP_island"
},
"blimp_coordinate_structure_constraint_complex_left_branch": {
"acc,none": 0.544,
"acc_stderr,none": 0.01575792855397918,
"alias": " - blimp_coordinate_structure_constraint_complex_left_branch"
},
"blimp_coordinate_structure_constraint_object_extraction": {
"acc,none": 0.525,
"acc_stderr,none": 0.015799513429996023,
"alias": " - blimp_coordinate_structure_constraint_object_extraction"
},
"blimp_determiner_noun_agreement_1": {
"acc,none": 0.526,
"acc_stderr,none": 0.015797897758042797,
"alias": " - blimp_determiner_noun_agreement_1"
},
"blimp_determiner_noun_agreement_2": {
"acc,none": 0.529,
"acc_stderr,none": 0.015792669451628764,
"alias": " - blimp_determiner_noun_agreement_2"
},
"blimp_determiner_noun_agreement_irregular_1": {
"acc,none": 0.531,
"acc_stderr,none": 0.015788865959538965,
"alias": " - blimp_determiner_noun_agreement_irregular_1"
},
"blimp_determiner_noun_agreement_irregular_2": {
"acc,none": 0.542,
"acc_stderr,none": 0.015763390640483554,
"alias": " - blimp_determiner_noun_agreement_irregular_2"
},
"blimp_determiner_noun_agreement_with_adj_2": {
"acc,none": 0.51,
"acc_stderr,none": 0.015816135752773183,
"alias": " - blimp_determiner_noun_agreement_with_adj_2"
},
"blimp_determiner_noun_agreement_with_adj_irregular_1": {
"acc,none": 0.515,
"acc_stderr,none": 0.01581217964181488,
"alias": " - blimp_determiner_noun_agreement_with_adj_irregular_1"
},
"blimp_determiner_noun_agreement_with_adj_irregular_2": {
"acc,none": 0.493,
"acc_stderr,none": 0.01581774956184353,
"alias": " - blimp_determiner_noun_agreement_with_adj_irregular_2"
},
"blimp_determiner_noun_agreement_with_adjective_1": {
"acc,none": 0.527,
"acc_stderr,none": 0.01579621855130273,
"alias": " - blimp_determiner_noun_agreement_with_adjective_1"
},
"blimp_distractor_agreement_relational_noun": {
"acc,none": 0.55,
"acc_stderr,none": 0.015740004693383918,
"alias": " - blimp_distractor_agreement_relational_noun"
},
"blimp_distractor_agreement_relative_clause": {
"acc,none": 0.547,
"acc_stderr,none": 0.015749255189977687,
"alias": " - blimp_distractor_agreement_relative_clause"
},
"blimp_drop_argument": {
"acc,none": 0.685,
"acc_stderr,none": 0.014696631960792617,
"alias": " - blimp_drop_argument"
},
"blimp_ellipsis_n_bar_1": {
"acc,none": 0.501,
"acc_stderr,none": 0.015819268290576817,
"alias": " - blimp_ellipsis_n_bar_1"
},
"blimp_ellipsis_n_bar_2": {
"acc,none": 0.327,
"acc_stderr,none": 0.014842213153411162,
"alias": " - blimp_ellipsis_n_bar_2"
},
"blimp_existential_there_object_raising": {
"acc,none": 0.685,
"acc_stderr,none": 0.014696631960792617,
"alias": " - blimp_existential_there_object_raising"
},
"blimp_existential_there_quantifiers_1": {
"acc,none": 0.613,
"acc_stderr,none": 0.015410011955494015,
"alias": " - blimp_existential_there_quantifiers_1"
},
"blimp_existential_there_quantifiers_2": {
"acc,none": 0.892,
"acc_stderr,none": 0.009820001651345708,
"alias": " - blimp_existential_there_quantifiers_2"
},
"blimp_existential_there_subject_raising": {
"acc,none": 0.491,
"acc_stderr,none": 0.0158167369950053,
"alias": " - blimp_existential_there_subject_raising"
},
"blimp_expletive_it_object_raising": {
"acc,none": 0.579,
"acc_stderr,none": 0.015620595475301287,
"alias": " - blimp_expletive_it_object_raising"
},
"blimp_inchoative": {
"acc,none": 0.434,
"acc_stderr,none": 0.015680876566375044,
"alias": " - blimp_inchoative"
},
"blimp_intransitive": {
"acc,none": 0.588,
"acc_stderr,none": 0.015572363292015072,
"alias": " - blimp_intransitive"
},
"blimp_irregular_past_participle_adjectives": {
"acc,none": 0.587,
"acc_stderr,none": 0.015577986829936457,
"alias": " - blimp_irregular_past_participle_adjectives"
},
"blimp_irregular_past_participle_verbs": {
"acc,none": 0.538,
"acc_stderr,none": 0.015773547629015002,
"alias": " - blimp_irregular_past_participle_verbs"
},
"blimp_irregular_plural_subject_verb_agreement_1": {
"acc,none": 0.514,
"acc_stderr,none": 0.01581309754773093,
"alias": " - blimp_irregular_plural_subject_verb_agreement_1"
},
"blimp_irregular_plural_subject_verb_agreement_2": {
"acc,none": 0.473,
"acc_stderr,none": 0.01579621855130273,
"alias": " - blimp_irregular_plural_subject_verb_agreement_2"
},
"blimp_left_branch_island_echo_question": {
"acc,none": 0.639,
"acc_stderr,none": 0.015195720118175049,
"alias": " - blimp_left_branch_island_echo_question"
},
"blimp_left_branch_island_simple_question": {
"acc,none": 0.509,
"acc_stderr,none": 0.0158167369950053,
"alias": " - blimp_left_branch_island_simple_question"
},
"blimp_matrix_question_npi_licensor_present": {
"acc,none": 0.392,
"acc_stderr,none": 0.015445859463771338,
"alias": " - blimp_matrix_question_npi_licensor_present"
},
"blimp_npi_present_1": {
"acc,none": 0.319,
"acc_stderr,none": 0.014746404865473364,
"alias": " - blimp_npi_present_1"
},
"blimp_npi_present_2": {
"acc,none": 0.227,
"acc_stderr,none": 0.013253174964763978,
"alias": " - blimp_npi_present_2"
},
"blimp_only_npi_licensor_present": {
"acc,none": 0.502,
"acc_stderr,none": 0.01581917337430266,
"alias": " - blimp_only_npi_licensor_present"
},
"blimp_only_npi_scope": {
"acc,none": 0.297,
"acc_stderr,none": 0.01445683229480096,
"alias": " - blimp_only_npi_scope"
},
"blimp_passive_1": {
"acc,none": 0.583,
"acc_stderr,none": 0.015599819048769583,
"alias": " - blimp_passive_1"
},
"blimp_passive_2": {
"acc,none": 0.614,
"acc_stderr,none": 0.015402637476784335,
"alias": " - blimp_passive_2"
},
"blimp_principle_A_c_command": {
"acc,none": 0.482,
"acc_stderr,none": 0.01580904569940659,
"alias": " - blimp_principle_A_c_command"
},
"blimp_principle_A_case_1": {
"acc,none": 0.365,
"acc_stderr,none": 0.015231776226264848,
"alias": " - blimp_principle_A_case_1"
},
"blimp_principle_A_case_2": {
"acc,none": 0.47,
"acc_stderr,none": 0.015790799515836725,
"alias": " - blimp_principle_A_case_2"
},
"blimp_principle_A_domain_1": {
"acc,none": 0.316,
"acc_stderr,none": 0.014709193056057165,
"alias": " - blimp_principle_A_domain_1"
},
"blimp_principle_A_domain_2": {
"acc,none": 0.453,
"acc_stderr,none": 0.015749255189977683,
"alias": " - blimp_principle_A_domain_2"
},
"blimp_principle_A_domain_3": {
"acc,none": 0.504,
"acc_stderr,none": 0.01581879370351084,
"alias": " - blimp_principle_A_domain_3"
},
"blimp_principle_A_reconstruction": {
"acc,none": 0.526,
"acc_stderr,none": 0.015797897758042797,
"alias": " - blimp_principle_A_reconstruction"
},
"blimp_regular_plural_subject_verb_agreement_1": {
"acc,none": 0.465,
"acc_stderr,none": 0.015780495050030086,
"alias": " - blimp_regular_plural_subject_verb_agreement_1"
},
"blimp_regular_plural_subject_verb_agreement_2": {
"acc,none": 0.508,
"acc_stderr,none": 0.015817274929209084,
"alias": " - blimp_regular_plural_subject_verb_agreement_2"
},
"blimp_sentential_negation_npi_licensor_present": {
"acc,none": 0.804,
"acc_stderr,none": 0.012559527926707347,
"alias": " - blimp_sentential_negation_npi_licensor_present"
},
"blimp_sentential_negation_npi_scope": {
"acc,none": 0.445,
"acc_stderr,none": 0.015723301886761007,
"alias": " - blimp_sentential_negation_npi_scope"
},
"blimp_sentential_subject_island": {
"acc,none": 0.527,
"acc_stderr,none": 0.01579621855130273,
"alias": " - blimp_sentential_subject_island"
},
"blimp_superlative_quantifiers_1": {
"acc,none": 0.391,
"acc_stderr,none": 0.015438826294681775,
"alias": " - blimp_superlative_quantifiers_1"
},
"blimp_superlative_quantifiers_2": {
"acc,none": 0.328,
"acc_stderr,none": 0.01485384248727031,
"alias": " - blimp_superlative_quantifiers_2"
},
"blimp_tough_vs_raising_1": {
"acc,none": 0.459,
"acc_stderr,none": 0.015766025737882314,
"alias": " - blimp_tough_vs_raising_1"
},
"blimp_tough_vs_raising_2": {
"acc,none": 0.563,
"acc_stderr,none": 0.01569322392873043,
"alias": " - blimp_tough_vs_raising_2"
},
"blimp_transitive": {
"acc,none": 0.508,
"acc_stderr,none": 0.015817274929209084,
"alias": " - blimp_transitive"
},
"blimp_wh_island": {
"acc,none": 0.489,
"acc_stderr,none": 0.01581547119529257,
"alias": " - blimp_wh_island"
},
"blimp_wh_questions_object_gap": {
"acc,none": 0.352,
"acc_stderr,none": 0.015110404505648562,
"alias": " - blimp_wh_questions_object_gap"
},
"blimp_wh_questions_subject_gap": {
"acc,none": 0.321,
"acc_stderr,none": 0.01477082181793475,
"alias": " - blimp_wh_questions_subject_gap"
},
"blimp_wh_questions_subject_gap_long_distance": {
"acc,none": 0.355,
"acc_stderr,none": 0.015139491543780598,
"alias": " - blimp_wh_questions_subject_gap_long_distance"
},
"blimp_wh_vs_that_no_gap": {
"acc,none": 0.42,
"acc_stderr,none": 0.015615500115072968,
"alias": " - blimp_wh_vs_that_no_gap"
},
"blimp_wh_vs_that_no_gap_long_distance": {
"acc,none": 0.408,
"acc_stderr,none": 0.015549205052920803,
"alias": " - blimp_wh_vs_that_no_gap_long_distance"
},
"blimp_wh_vs_that_with_gap": {
"acc,none": 0.611,
"acc_stderr,none": 0.015424555647308514,
"alias": " - blimp_wh_vs_that_with_gap"
},
"blimp_wh_vs_that_with_gap_long_distance": {
"acc,none": 0.65,
"acc_stderr,none": 0.015090650341444127,
"alias": " - blimp_wh_vs_that_with_gap_long_distance"
}
} | {
"blimp": {
"acc,none": 0.5102835820895523,
"acc_stderr,none": 0.0018749288807151285,
"alias": "blimp"
}
} | {
"blimp": [
"blimp_causative",
"blimp_determiner_noun_agreement_irregular_2",
"blimp_passive_1",
"blimp_wh_questions_subject_gap",
"blimp_irregular_plural_subject_verb_agreement_1",
"blimp_wh_vs_that_no_gap",
"blimp_complex_NP_island",
"blimp_principle_A_reconstruction",
"blimp_anaphor_number_agreement",
"blimp_principle_A_domain_3",
"blimp_anaphor_gender_agreement",
"blimp_irregular_past_participle_adjectives",
"blimp_regular_plural_subject_verb_agreement_1",
"blimp_sentential_subject_island",
"blimp_left_branch_island_simple_question",
"blimp_distractor_agreement_relative_clause",
"blimp_irregular_plural_subject_verb_agreement_2",
"blimp_left_branch_island_echo_question",
"blimp_wh_vs_that_no_gap_long_distance",
"blimp_ellipsis_n_bar_1",
"blimp_determiner_noun_agreement_1",
"blimp_superlative_quantifiers_2",
"blimp_ellipsis_n_bar_2",
"blimp_adjunct_island",
"blimp_expletive_it_object_raising",
"blimp_principle_A_c_command",
"blimp_principle_A_domain_1",
"blimp_superlative_quantifiers_1",
"blimp_only_npi_scope",
"blimp_tough_vs_raising_1",
"blimp_transitive",
"blimp_intransitive",
"blimp_wh_questions_object_gap",
"blimp_only_npi_licensor_present",
"blimp_wh_vs_that_with_gap",
"blimp_existential_there_quantifiers_1",
"blimp_coordinate_structure_constraint_complex_left_branch",
"blimp_principle_A_domain_2",
"blimp_determiner_noun_agreement_with_adj_2",
"blimp_wh_island",
"blimp_existential_there_quantifiers_2",
"blimp_existential_there_object_raising",
"blimp_determiner_noun_agreement_with_adj_irregular_1",
"blimp_npi_present_2",
"blimp_animate_subject_passive",
"blimp_wh_questions_subject_gap_long_distance",
"blimp_existential_there_subject_raising",
"blimp_principle_A_case_2",
"blimp_principle_A_case_1",
"blimp_wh_vs_that_with_gap_long_distance",
"blimp_determiner_noun_agreement_irregular_1",
"blimp_drop_argument",
"blimp_sentential_negation_npi_scope",
"blimp_coordinate_structure_constraint_object_extraction",
"blimp_determiner_noun_agreement_2",
"blimp_irregular_past_participle_verbs",
"blimp_tough_vs_raising_2",
"blimp_sentential_negation_npi_licensor_present",
"blimp_distractor_agreement_relational_noun",
"blimp_passive_2",
"blimp_determiner_noun_agreement_with_adjective_1",
"blimp_inchoative",
"blimp_animate_subject_trans",
"blimp_regular_plural_subject_verb_agreement_2",
"blimp_npi_present_1",
"blimp_determiner_noun_agreement_with_adj_irregular_2",
"blimp_matrix_question_npi_licensor_present"
]
} | {
"blimp_adjunct_island": {
"task": "blimp_adjunct_island",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "adjunct_island",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_anaphor_gender_agreement": {
"task": "blimp_anaphor_gender_agreement",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "anaphor_gender_agreement",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_anaphor_number_agreement": {
"task": "blimp_anaphor_number_agreement",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "anaphor_number_agreement",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_animate_subject_passive": {
"task": "blimp_animate_subject_passive",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "animate_subject_passive",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_animate_subject_trans": {
"task": "blimp_animate_subject_trans",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "animate_subject_trans",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_causative": {
"task": "blimp_causative",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "causative",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_complex_NP_island": {
"task": "blimp_complex_NP_island",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "complex_NP_island",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_coordinate_structure_constraint_complex_left_branch": {
"task": "blimp_coordinate_structure_constraint_complex_left_branch",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "coordinate_structure_constraint_complex_left_branch",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_coordinate_structure_constraint_object_extraction": {
"task": "blimp_coordinate_structure_constraint_object_extraction",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "coordinate_structure_constraint_object_extraction",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_determiner_noun_agreement_1": {
"task": "blimp_determiner_noun_agreement_1",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "determiner_noun_agreement_1",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_determiner_noun_agreement_2": {
"task": "blimp_determiner_noun_agreement_2",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "determiner_noun_agreement_2",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_determiner_noun_agreement_irregular_1": {
"task": "blimp_determiner_noun_agreement_irregular_1",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "determiner_noun_agreement_irregular_1",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_determiner_noun_agreement_irregular_2": {
"task": "blimp_determiner_noun_agreement_irregular_2",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "determiner_noun_agreement_irregular_2",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_determiner_noun_agreement_with_adj_2": {
"task": "blimp_determiner_noun_agreement_with_adj_2",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "determiner_noun_agreement_with_adj_2",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_determiner_noun_agreement_with_adj_irregular_1": {
"task": "blimp_determiner_noun_agreement_with_adj_irregular_1",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "determiner_noun_agreement_with_adj_irregular_1",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_determiner_noun_agreement_with_adj_irregular_2": {
"task": "blimp_determiner_noun_agreement_with_adj_irregular_2",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "determiner_noun_agreement_with_adj_irregular_2",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_determiner_noun_agreement_with_adjective_1": {
"task": "blimp_determiner_noun_agreement_with_adjective_1",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "determiner_noun_agreement_with_adjective_1",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_distractor_agreement_relational_noun": {
"task": "blimp_distractor_agreement_relational_noun",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "distractor_agreement_relational_noun",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_distractor_agreement_relative_clause": {
"task": "blimp_distractor_agreement_relative_clause",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "distractor_agreement_relative_clause",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_drop_argument": {
"task": "blimp_drop_argument",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "drop_argument",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_ellipsis_n_bar_1": {
"task": "blimp_ellipsis_n_bar_1",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "ellipsis_n_bar_1",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_ellipsis_n_bar_2": {
"task": "blimp_ellipsis_n_bar_2",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "ellipsis_n_bar_2",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_existential_there_object_raising": {
"task": "blimp_existential_there_object_raising",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "existential_there_object_raising",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_existential_there_quantifiers_1": {
"task": "blimp_existential_there_quantifiers_1",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "existential_there_quantifiers_1",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_existential_there_quantifiers_2": {
"task": "blimp_existential_there_quantifiers_2",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "existential_there_quantifiers_2",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_existential_there_subject_raising": {
"task": "blimp_existential_there_subject_raising",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "existential_there_subject_raising",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_expletive_it_object_raising": {
"task": "blimp_expletive_it_object_raising",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "expletive_it_object_raising",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_inchoative": {
"task": "blimp_inchoative",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "inchoative",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_intransitive": {
"task": "blimp_intransitive",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "intransitive",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_irregular_past_participle_adjectives": {
"task": "blimp_irregular_past_participle_adjectives",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "irregular_past_participle_adjectives",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_irregular_past_participle_verbs": {
"task": "blimp_irregular_past_participle_verbs",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "irregular_past_participle_verbs",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_irregular_plural_subject_verb_agreement_1": {
"task": "blimp_irregular_plural_subject_verb_agreement_1",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "irregular_plural_subject_verb_agreement_1",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_irregular_plural_subject_verb_agreement_2": {
"task": "blimp_irregular_plural_subject_verb_agreement_2",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "irregular_plural_subject_verb_agreement_2",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_left_branch_island_echo_question": {
"task": "blimp_left_branch_island_echo_question",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "left_branch_island_echo_question",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_left_branch_island_simple_question": {
"task": "blimp_left_branch_island_simple_question",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "left_branch_island_simple_question",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_matrix_question_npi_licensor_present": {
"task": "blimp_matrix_question_npi_licensor_present",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "matrix_question_npi_licensor_present",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_npi_present_1": {
"task": "blimp_npi_present_1",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "npi_present_1",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_npi_present_2": {
"task": "blimp_npi_present_2",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "npi_present_2",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_only_npi_licensor_present": {
"task": "blimp_only_npi_licensor_present",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "only_npi_licensor_present",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_only_npi_scope": {
"task": "blimp_only_npi_scope",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "only_npi_scope",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_passive_1": {
"task": "blimp_passive_1",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "passive_1",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_passive_2": {
"task": "blimp_passive_2",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "passive_2",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_principle_A_c_command": {
"task": "blimp_principle_A_c_command",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "principle_A_c_command",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_principle_A_case_1": {
"task": "blimp_principle_A_case_1",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "principle_A_case_1",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_principle_A_case_2": {
"task": "blimp_principle_A_case_2",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "principle_A_case_2",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_principle_A_domain_1": {
"task": "blimp_principle_A_domain_1",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "principle_A_domain_1",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_principle_A_domain_2": {
"task": "blimp_principle_A_domain_2",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "principle_A_domain_2",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_principle_A_domain_3": {
"task": "blimp_principle_A_domain_3",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "principle_A_domain_3",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_principle_A_reconstruction": {
"task": "blimp_principle_A_reconstruction",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "principle_A_reconstruction",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_regular_plural_subject_verb_agreement_1": {
"task": "blimp_regular_plural_subject_verb_agreement_1",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "regular_plural_subject_verb_agreement_1",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_regular_plural_subject_verb_agreement_2": {
"task": "blimp_regular_plural_subject_verb_agreement_2",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "regular_plural_subject_verb_agreement_2",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_sentential_negation_npi_licensor_present": {
"task": "blimp_sentential_negation_npi_licensor_present",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "sentential_negation_npi_licensor_present",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_sentential_negation_npi_scope": {
"task": "blimp_sentential_negation_npi_scope",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "sentential_negation_npi_scope",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_sentential_subject_island": {
"task": "blimp_sentential_subject_island",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "sentential_subject_island",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_superlative_quantifiers_1": {
"task": "blimp_superlative_quantifiers_1",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "superlative_quantifiers_1",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_superlative_quantifiers_2": {
"task": "blimp_superlative_quantifiers_2",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "superlative_quantifiers_2",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_tough_vs_raising_1": {
"task": "blimp_tough_vs_raising_1",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "tough_vs_raising_1",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_tough_vs_raising_2": {
"task": "blimp_tough_vs_raising_2",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "tough_vs_raising_2",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_transitive": {
"task": "blimp_transitive",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "transitive",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_wh_island": {
"task": "blimp_wh_island",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "wh_island",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_wh_questions_object_gap": {
"task": "blimp_wh_questions_object_gap",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "wh_questions_object_gap",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_wh_questions_subject_gap": {
"task": "blimp_wh_questions_subject_gap",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "wh_questions_subject_gap",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_wh_questions_subject_gap_long_distance": {
"task": "blimp_wh_questions_subject_gap_long_distance",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "wh_questions_subject_gap_long_distance",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_wh_vs_that_no_gap": {
"task": "blimp_wh_vs_that_no_gap",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "wh_vs_that_no_gap",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_wh_vs_that_no_gap_long_distance": {
"task": "blimp_wh_vs_that_no_gap_long_distance",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "wh_vs_that_no_gap_long_distance",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_wh_vs_that_with_gap": {
"task": "blimp_wh_vs_that_with_gap",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "wh_vs_that_with_gap",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
},
"blimp_wh_vs_that_with_gap_long_distance": {
"task": "blimp_wh_vs_that_with_gap_long_distance",
"group": "blimp",
"dataset_path": "blimp",
"dataset_name": "wh_vs_that_with_gap_long_distance",
"validation_split": "train",
"doc_to_text": "",
"doc_to_target": 0,
"doc_to_choice": "{{[sentence_good, sentence_bad]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "acc"
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
"metadata": {
"version": 1
}
}
} | {
"blimp_adjunct_island": 1,
"blimp_anaphor_gender_agreement": 1,
"blimp_anaphor_number_agreement": 1,
"blimp_animate_subject_passive": 1,
"blimp_animate_subject_trans": 1,
"blimp_causative": 1,
"blimp_complex_NP_island": 1,
"blimp_coordinate_structure_constraint_complex_left_branch": 1,
"blimp_coordinate_structure_constraint_object_extraction": 1,
"blimp_determiner_noun_agreement_1": 1,
"blimp_determiner_noun_agreement_2": 1,
"blimp_determiner_noun_agreement_irregular_1": 1,
"blimp_determiner_noun_agreement_irregular_2": 1,
"blimp_determiner_noun_agreement_with_adj_2": 1,
"blimp_determiner_noun_agreement_with_adj_irregular_1": 1,
"blimp_determiner_noun_agreement_with_adj_irregular_2": 1,
"blimp_determiner_noun_agreement_with_adjective_1": 1,
"blimp_distractor_agreement_relational_noun": 1,
"blimp_distractor_agreement_relative_clause": 1,
"blimp_drop_argument": 1,
"blimp_ellipsis_n_bar_1": 1,
"blimp_ellipsis_n_bar_2": 1,
"blimp_existential_there_object_raising": 1,
"blimp_existential_there_quantifiers_1": 1,
"blimp_existential_there_quantifiers_2": 1,
"blimp_existential_there_subject_raising": 1,
"blimp_expletive_it_object_raising": 1,
"blimp_inchoative": 1,
"blimp_intransitive": 1,
"blimp_irregular_past_participle_adjectives": 1,
"blimp_irregular_past_participle_verbs": 1,
"blimp_irregular_plural_subject_verb_agreement_1": 1,
"blimp_irregular_plural_subject_verb_agreement_2": 1,
"blimp_left_branch_island_echo_question": 1,
"blimp_left_branch_island_simple_question": 1,
"blimp_matrix_question_npi_licensor_present": 1,
"blimp_npi_present_1": 1,
"blimp_npi_present_2": 1,
"blimp_only_npi_licensor_present": 1,
"blimp_only_npi_scope": 1,
"blimp_passive_1": 1,
"blimp_passive_2": 1,
"blimp_principle_A_c_command": 1,
"blimp_principle_A_case_1": 1,
"blimp_principle_A_case_2": 1,
"blimp_principle_A_domain_1": 1,
"blimp_principle_A_domain_2": 1,
"blimp_principle_A_domain_3": 1,
"blimp_principle_A_reconstruction": 1,
"blimp_regular_plural_subject_verb_agreement_1": 1,
"blimp_regular_plural_subject_verb_agreement_2": 1,
"blimp_sentential_negation_npi_licensor_present": 1,
"blimp_sentential_negation_npi_scope": 1,
"blimp_sentential_subject_island": 1,
"blimp_superlative_quantifiers_1": 1,
"blimp_superlative_quantifiers_2": 1,
"blimp_tough_vs_raising_1": 1,
"blimp_tough_vs_raising_2": 1,
"blimp_transitive": 1,
"blimp_wh_island": 1,
"blimp_wh_questions_object_gap": 1,
"blimp_wh_questions_subject_gap": 1,
"blimp_wh_questions_subject_gap_long_distance": 1,
"blimp_wh_vs_that_no_gap": 1,
"blimp_wh_vs_that_no_gap_long_distance": 1,
"blimp_wh_vs_that_with_gap": 1,
"blimp_wh_vs_that_with_gap_long_distance": 1
} | {
"blimp": 0,
"blimp_adjunct_island": 0,
"blimp_anaphor_gender_agreement": 0,
"blimp_anaphor_number_agreement": 0,
"blimp_animate_subject_passive": 0,
"blimp_animate_subject_trans": 0,
"blimp_causative": 0,
"blimp_complex_NP_island": 0,
"blimp_coordinate_structure_constraint_complex_left_branch": 0,
"blimp_coordinate_structure_constraint_object_extraction": 0,
"blimp_determiner_noun_agreement_1": 0,
"blimp_determiner_noun_agreement_2": 0,
"blimp_determiner_noun_agreement_irregular_1": 0,
"blimp_determiner_noun_agreement_irregular_2": 0,
"blimp_determiner_noun_agreement_with_adj_2": 0,
"blimp_determiner_noun_agreement_with_adj_irregular_1": 0,
"blimp_determiner_noun_agreement_with_adj_irregular_2": 0,
"blimp_determiner_noun_agreement_with_adjective_1": 0,
"blimp_distractor_agreement_relational_noun": 0,
"blimp_distractor_agreement_relative_clause": 0,
"blimp_drop_argument": 0,
"blimp_ellipsis_n_bar_1": 0,
"blimp_ellipsis_n_bar_2": 0,
"blimp_existential_there_object_raising": 0,
"blimp_existential_there_quantifiers_1": 0,
"blimp_existential_there_quantifiers_2": 0,
"blimp_existential_there_subject_raising": 0,
"blimp_expletive_it_object_raising": 0,
"blimp_inchoative": 0,
"blimp_intransitive": 0,
"blimp_irregular_past_participle_adjectives": 0,
"blimp_irregular_past_participle_verbs": 0,
"blimp_irregular_plural_subject_verb_agreement_1": 0,
"blimp_irregular_plural_subject_verb_agreement_2": 0,
"blimp_left_branch_island_echo_question": 0,
"blimp_left_branch_island_simple_question": 0,
"blimp_matrix_question_npi_licensor_present": 0,
"blimp_npi_present_1": 0,
"blimp_npi_present_2": 0,
"blimp_only_npi_licensor_present": 0,
"blimp_only_npi_scope": 0,
"blimp_passive_1": 0,
"blimp_passive_2": 0,
"blimp_principle_A_c_command": 0,
"blimp_principle_A_case_1": 0,
"blimp_principle_A_case_2": 0,
"blimp_principle_A_domain_1": 0,
"blimp_principle_A_domain_2": 0,
"blimp_principle_A_domain_3": 0,
"blimp_principle_A_reconstruction": 0,
"blimp_regular_plural_subject_verb_agreement_1": 0,
"blimp_regular_plural_subject_verb_agreement_2": 0,
"blimp_sentential_negation_npi_licensor_present": 0,
"blimp_sentential_negation_npi_scope": 0,
"blimp_sentential_subject_island": 0,
"blimp_superlative_quantifiers_1": 0,
"blimp_superlative_quantifiers_2": 0,
"blimp_tough_vs_raising_1": 0,
"blimp_tough_vs_raising_2": 0,
"blimp_transitive": 0,
"blimp_wh_island": 0,
"blimp_wh_questions_object_gap": 0,
"blimp_wh_questions_subject_gap": 0,
"blimp_wh_questions_subject_gap_long_distance": 0,
"blimp_wh_vs_that_no_gap": 0,
"blimp_wh_vs_that_no_gap_long_distance": 0,
"blimp_wh_vs_that_with_gap": 0,
"blimp_wh_vs_that_with_gap_long_distance": 0
} | {
"blimp_causative": {
"original": 1000,
"effective": 1000
},
"blimp_determiner_noun_agreement_irregular_2": {
"original": 1000,
"effective": 1000
},
"blimp_passive_1": {
"original": 1000,
"effective": 1000
},
"blimp_wh_questions_subject_gap": {
"original": 1000,
"effective": 1000
},
"blimp_irregular_plural_subject_verb_agreement_1": {
"original": 1000,
"effective": 1000
},
"blimp_wh_vs_that_no_gap": {
"original": 1000,
"effective": 1000
},
"blimp_complex_NP_island": {
"original": 1000,
"effective": 1000
},
"blimp_principle_A_reconstruction": {
"original": 1000,
"effective": 1000
},
"blimp_anaphor_number_agreement": {
"original": 1000,
"effective": 1000
},
"blimp_principle_A_domain_3": {
"original": 1000,
"effective": 1000
},
"blimp_anaphor_gender_agreement": {
"original": 1000,
"effective": 1000
},
"blimp_irregular_past_participle_adjectives": {
"original": 1000,
"effective": 1000
},
"blimp_regular_plural_subject_verb_agreement_1": {
"original": 1000,
"effective": 1000
},
"blimp_sentential_subject_island": {
"original": 1000,
"effective": 1000
},
"blimp_left_branch_island_simple_question": {
"original": 1000,
"effective": 1000
},
"blimp_distractor_agreement_relative_clause": {
"original": 1000,
"effective": 1000
},
"blimp_irregular_plural_subject_verb_agreement_2": {
"original": 1000,
"effective": 1000
},
"blimp_left_branch_island_echo_question": {
"original": 1000,
"effective": 1000
},
"blimp_wh_vs_that_no_gap_long_distance": {
"original": 1000,
"effective": 1000
},
"blimp_ellipsis_n_bar_1": {
"original": 1000,
"effective": 1000
},
"blimp_determiner_noun_agreement_1": {
"original": 1000,
"effective": 1000
},
"blimp_superlative_quantifiers_2": {
"original": 1000,
"effective": 1000
},
"blimp_ellipsis_n_bar_2": {
"original": 1000,
"effective": 1000
},
"blimp_adjunct_island": {
"original": 1000,
"effective": 1000
},
"blimp_expletive_it_object_raising": {
"original": 1000,
"effective": 1000
},
"blimp_principle_A_c_command": {
"original": 1000,
"effective": 1000
},
"blimp_principle_A_domain_1": {
"original": 1000,
"effective": 1000
},
"blimp_superlative_quantifiers_1": {
"original": 1000,
"effective": 1000
},
"blimp_only_npi_scope": {
"original": 1000,
"effective": 1000
},
"blimp_tough_vs_raising_1": {
"original": 1000,
"effective": 1000
},
"blimp_transitive": {
"original": 1000,
"effective": 1000
},
"blimp_intransitive": {
"original": 1000,
"effective": 1000
},
"blimp_wh_questions_object_gap": {
"original": 1000,
"effective": 1000
},
"blimp_only_npi_licensor_present": {
"original": 1000,
"effective": 1000
},
"blimp_wh_vs_that_with_gap": {
"original": 1000,
"effective": 1000
},
"blimp_existential_there_quantifiers_1": {
"original": 1000,
"effective": 1000
},
"blimp_coordinate_structure_constraint_complex_left_branch": {
"original": 1000,
"effective": 1000
},
"blimp_principle_A_domain_2": {
"original": 1000,
"effective": 1000
},
"blimp_determiner_noun_agreement_with_adj_2": {
"original": 1000,
"effective": 1000
},
"blimp_wh_island": {
"original": 1000,
"effective": 1000
},
"blimp_existential_there_quantifiers_2": {
"original": 1000,
"effective": 1000
},
"blimp_existential_there_object_raising": {
"original": 1000,
"effective": 1000
},
"blimp_determiner_noun_agreement_with_adj_irregular_1": {
"original": 1000,
"effective": 1000
},
"blimp_npi_present_2": {
"original": 1000,
"effective": 1000
},
"blimp_animate_subject_passive": {
"original": 1000,
"effective": 1000
},
"blimp_wh_questions_subject_gap_long_distance": {
"original": 1000,
"effective": 1000
},
"blimp_existential_there_subject_raising": {
"original": 1000,
"effective": 1000
},
"blimp_principle_A_case_2": {
"original": 1000,
"effective": 1000
},
"blimp_principle_A_case_1": {
"original": 1000,
"effective": 1000
},
"blimp_wh_vs_that_with_gap_long_distance": {
"original": 1000,
"effective": 1000
},
"blimp_determiner_noun_agreement_irregular_1": {
"original": 1000,
"effective": 1000
},
"blimp_drop_argument": {
"original": 1000,
"effective": 1000
},
"blimp_sentential_negation_npi_scope": {
"original": 1000,
"effective": 1000
},
"blimp_coordinate_structure_constraint_object_extraction": {
"original": 1000,
"effective": 1000
},
"blimp_determiner_noun_agreement_2": {
"original": 1000,
"effective": 1000
},
"blimp_irregular_past_participle_verbs": {
"original": 1000,
"effective": 1000
},
"blimp_tough_vs_raising_2": {
"original": 1000,
"effective": 1000
},
"blimp_sentential_negation_npi_licensor_present": {
"original": 1000,
"effective": 1000
},
"blimp_distractor_agreement_relational_noun": {
"original": 1000,
"effective": 1000
},
"blimp_passive_2": {
"original": 1000,
"effective": 1000
},
"blimp_determiner_noun_agreement_with_adjective_1": {
"original": 1000,
"effective": 1000
},
"blimp_inchoative": {
"original": 1000,
"effective": 1000
},
"blimp_animate_subject_trans": {
"original": 1000,
"effective": 1000
},
"blimp_regular_plural_subject_verb_agreement_2": {
"original": 1000,
"effective": 1000
},
"blimp_npi_present_1": {
"original": 1000,
"effective": 1000
},
"blimp_determiner_noun_agreement_with_adj_irregular_2": {
"original": 1000,
"effective": 1000
},
"blimp_matrix_question_npi_licensor_present": {
"original": 1000,
"effective": 1000
}
} | {
"model": "hf",
"model_args": "pretrained=EleutherAI/pythia-14m,revision=step0",
"model_num_parameters": 14067712,
"model_dtype": "torch.float16",
"model_revision": "step0",
"model_sha": "bc249c50b4a381f99e9296f08a69b8562a31fde4",
"batch_size": "1024",
"batch_sizes": [],
"device": "cuda",
"use_cache": null,
"limit": null,
"bootstrap_iters": 100000,
"gen_kwargs": null,
"random_seed": 0,
"numpy_seed": 1234,
"torch_seed": 1234,
"fewshot_seed": 1234
} | 51a7ca9 | 1,720,429,466.869086 | PyTorch version: 2.3.0+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A
OS: CentOS Linux release 7.9.2009 (Core) (x86_64)
GCC version: (GCC) 12.1.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.17
Python version: 3.12.1 (main, Jan 12 2024, 16:49:08) [GCC 12.1.0] (64-bit runtime)
Python platform: Linux-3.10.0-1160.119.1.el7.x86_64-x86_64-with-glibc2.17
Is CUDA available: True
CUDA runtime version: 12.4.99
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: Tesla V100S-PCIE-32GB
Nvidia driver version: 550.90.07
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
CPU(s): 32
On-line CPU(s) list: 0-31
Thread(s) per core: 1
Core(s) per socket: 32
Socket(s): 1
NUMA node(s): 2
Vendor ID: AuthenticAMD
CPU family: 23
Model: 49
Model name: AMD EPYC 7502P 32-Core Processor
Stepping: 0
CPU MHz: 1500.000
CPU max MHz: 2500.0000
CPU min MHz: 1500.0000
BogoMIPS: 5000.46
Virtualization: AMD-V
L1d cache: 32K
L1i cache: 32K
L2 cache: 512K
L3 cache: 16384K
NUMA node0 CPU(s): 0-15
NUMA node1 CPU(s): 16-31
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc art rep_good nopl nonstop_tsc extd_apicid aperfmperf eagerfpu pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_l2 cpb cat_l3 cdp_l3 hw_pstate sme ssbd ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif umip overflow_recov succor smca
Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] torch==2.3.0
[conda] Could not collect | 4.40.2 | null | {} | hf | EleutherAI/pythia-14m | EleutherAI__pythia-14m | 753,492.986263 | 753,904.208267 | 411.22200435004197 |
{
"lambada_openai": {
"perplexity,none": 3507781.8105202965,
"perplexity_stderr,none": 338907.2426000304,
"acc,none": 0,
"acc_stderr,none": 0,
"alias": "lambada_openai"
}
} | null | {
"lambada_openai": []
} | {
"lambada_openai": {
"task": "lambada_openai",
"group": [
"lambada"
],
"dataset_path": "EleutherAI/lambada_openai",
"dataset_name": "default",
"dataset_kwargs": {
"trust_remote_code": true
},
"test_split": "test",
"doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
"doc_to_target": "{{' '+text.split(' ')[-1]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "perplexity",
"aggregation": "perplexity",
"higher_is_better": false
},
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "loglikelihood",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "{{text}}",
"metadata": {
"version": 1
}
}
} | {
"lambada_openai": 1
} | {
"lambada_openai": 0
} | {
"lambada_openai": {
"original": 5153,
"effective": 5153
}
} | {
"model": "hf",
"model_args": "pretrained=EleutherAI/pythia-14m,revision=step0,",
"model_num_parameters": 14067712,
"model_dtype": "torch.float16",
"model_revision": "step0",
"model_sha": "bc249c50b4a381f99e9296f08a69b8562a31fde4",
"batch_size": "128",
"batch_sizes": [],
"device": "cuda",
"use_cache": null,
"limit": null,
"bootstrap_iters": 100000,
"gen_kwargs": null,
"random_seed": 0,
"numpy_seed": 1234,
"torch_seed": 1234,
"fewshot_seed": 1234
} | 51a7ca9 | 1,723,751,264.258567 | PyTorch version: 2.3.0+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A
OS: CentOS Linux release 7.9.2009 (Core) (x86_64)
GCC version: (GCC) 12.1.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.17
Python version: 3.12.1 (main, Jan 12 2024, 16:49:08) [GCC 12.1.0] (64-bit runtime)
Python platform: Linux-3.10.0-1160.119.1.el7.tuxcare.els2.x86_64-x86_64-with-glibc2.17
Is CUDA available: True
CUDA runtime version: 12.4.99
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: Tesla V100S-PCIE-32GB
Nvidia driver version: 550.90.07
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
CPU(s): 32
On-line CPU(s) list: 0-31
Thread(s) per core: 1
Core(s) per socket: 32
Socket(s): 1
NUMA node(s): 2
Vendor ID: AuthenticAMD
CPU family: 23
Model: 49
Model name: AMD EPYC 7502P 32-Core Processor
Stepping: 0
CPU MHz: 1500.000
CPU max MHz: 2500.0000
CPU min MHz: 1500.0000
BogoMIPS: 5000.08
Virtualization: AMD-V
L1d cache: 32K
L1i cache: 32K
L2 cache: 512K
L3 cache: 16384K
NUMA node0 CPU(s): 0-15
NUMA node1 CPU(s): 16-31
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc art rep_good nopl nonstop_tsc extd_apicid aperfmperf eagerfpu pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_l2 cpb cat_l3 cdp_l3 hw_pstate sme ssbd ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif umip overflow_recov succor smca
Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] torch==2.3.0
[conda] Could not collect | 4.40.2 | null | {} | hf | EleutherAI/pythia-14m | EleutherAI__pythia-14m | 1,133,831.651543 | 1,133,915.107704 | 83.45616106898524 |
{
"simple_cooccurrence_bias": {
"likelihood_diff,none": -0.31463995695410724,
"likelihood_diff_stderr,none": 0.01165886599756874,
"pct_male_preferred,none": 0.8746438746438746,
"pct_male_preferred_stderr,none": 0.017699230587944016,
"alias": "simple_cooccurrence_bias"
}
} | null | {
"simple_cooccurrence_bias": []
} | {
"simple_cooccurrence_bias": {
"task": "simple_cooccurrence_bias",
"group": [
"social_bias"
],
"dataset_path": "oskarvanderwal/simple-cooccurrence-bias",
"test_split": "test",
"doc_to_text": "{{sentence}}",
"doc_to_target": [
0,
1
],
"doc_to_choice": [
"female",
"woman",
"male",
"man"
],
"process_results": "def process_results(doc, results):\n lls, _ = zip(*results)\n\n # likelihoods of \"female\", \"woman\", \"male\", \"man\", respectively\n likelihood1, likelihood2, likelihood3, likelihood4 = lls\n \n # Calculate the difference in loglikelihoods\n diff = math.log(math.exp(likelihood1) + math.exp(likelihood2)) - math.log(math.exp(likelihood3) + math.exp(likelihood4))\n\n # if male identifiers more likely (loglikelihood highest)\n # then treat this as predicting stereotyped sentence\n max_index = np.array([likelihood1,likelihood2,likelihood3,likelihood4]).argmax()\n acc = 1.0 if max_index > 1 else 0.0\n\n return {\"likelihood_diff\": diff, \"pct_male_preferred\": acc}\n",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"metric_list": [
{
"metric": "likelihood_diff",
"aggregation": "mean",
"higher_is_better": false
},
{
"metric": "pct_male_preferred",
"aggregation": "mean",
"higher_is_better": false
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1,
"num_fewshot": 0
}
}
} | {
"simple_cooccurrence_bias": 1
} | {
"simple_cooccurrence_bias": 0
} | {
"simple_cooccurrence_bias": {
"original": 351,
"effective": 351
}
} | {
"model": "hf",
"model_args": "pretrained=EleutherAI/pythia-14m,revision=step0",
"model_num_parameters": 14067712,
"model_dtype": "torch.float16",
"model_revision": "step0",
"model_sha": "bc249c50b4a381f99e9296f08a69b8562a31fde4",
"batch_size": "1024",
"batch_sizes": [],
"device": "cuda",
"use_cache": null,
"limit": null,
"bootstrap_iters": 100000,
"gen_kwargs": null,
"random_seed": 0,
"numpy_seed": 1234,
"torch_seed": 1234,
"fewshot_seed": 1234
} | 51a7ca9 | 1,724,408,842.463424 | PyTorch version: 2.4.0+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A
OS: CentOS Linux release 7.9.2009 (Core) (x86_64)
GCC version: (GCC) 12.1.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.17
Python version: 3.9.0 (default, Oct 6 2020, 11:01:41) [GCC 4.8.5 20150623 (Red Hat 4.8.5-36)] (64-bit runtime)
Python platform: Linux-3.10.0-1160.114.2.el7.x86_64-x86_64-with-glibc2.17
Is CUDA available: True
CUDA runtime version: 12.4.99
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: Tesla V100-SXM2-32GB
Nvidia driver version: 550.54.15
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
CPU(s): 24
On-line CPU(s) list: 0-23
Thread(s) per core: 1
Core(s) per socket: 12
Socket(s): 2
NUMA node(s): 2
Vendor ID: GenuineIntel
CPU family: 6
Model: 85
Model name: Intel(R) Xeon(R) Gold 5118 CPU @ 2.30GHz
Stepping: 4
CPU MHz: 2902.655
CPU max MHz: 3200.0000
CPU min MHz: 1000.0000
BogoMIPS: 4600.00
Virtualization: VT-x
L1d cache: 32K
L1i cache: 32K
L2 cache: 1024K
L3 cache: 16896K
NUMA node0 CPU(s): 0,2,4,6,8,10,12,14,16,18,20,22
NUMA node1 CPU(s): 1,3,5,7,9,11,13,15,17,19,21,23
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc aperfmperf eagerfpu pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch epb cat_l3 cdp_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts pku ospke md_clear spec_ctrl intel_stibp flush_l1d arch_capabilities
Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] torch==2.4.0
[pip3] triton==3.0.0
[conda] Could not collect | 4.44.0 | null | {} | hf | EleutherAI/pythia-14m | EleutherAI__pythia-14m | 4,697,201.426428 | 4,697,253.040466 | 51.61403867881745 |
{"blimp":{"acc,none":0.5102835820895523,"acc_stderr,none":0.0018749288807151285,"alias":"blimp"},"bl(...TRUNCATED) | {
"blimp": {
"acc,none": 0.5102835820895523,
"acc_stderr,none": 0.0018749288807151285,
"alias": "blimp"
}
} | {"blimp":["blimp_causative","blimp_determiner_noun_agreement_irregular_2","blimp_passive_1","blimp_w(...TRUNCATED) | {"blimp_adjunct_island":{"task":"blimp_adjunct_island","group":"blimp","dataset_path":"blimp","datas(...TRUNCATED) | {"blimp_adjunct_island":1.0,"blimp_anaphor_gender_agreement":1.0,"blimp_anaphor_number_agreement":1.(...TRUNCATED) | {"blimp":0,"blimp_adjunct_island":0,"blimp_anaphor_gender_agreement":0,"blimp_anaphor_number_agreeme(...TRUNCATED) | {"blimp_causative":{"original":1000,"effective":1000},"blimp_determiner_noun_agreement_irregular_2":(...TRUNCATED) | {"model":"hf","model_args":"pretrained=EleutherAI/pythia-14m,revision=step1","model_num_parameters":(...TRUNCATED) | 51a7ca9 | 1,720,429,852.278012 | "PyTorch version: 2.3.0+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to(...TRUNCATED) | 4.40.2 | null | {} | hf | EleutherAI/pythia-14m | EleutherAI__pythia-14m | 753,927.127344 | 754,281.841991 | 354.71464768901933 |
{"lambada_openai":{"perplexity,none":3507781.8105202965,"perplexity_stderr,none":338907.2426000304,"(...TRUNCATED) | null | {
"lambada_openai": []
} | {"lambada_openai":{"task":"lambada_openai","group":["lambada"],"dataset_path":"EleutherAI/lambada_op(...TRUNCATED) | {
"lambada_openai": 1
} | {
"lambada_openai": 0
} | {
"lambada_openai": {
"original": 5153,
"effective": 5153
}
} | {"model":"hf","model_args":"pretrained=EleutherAI/pythia-14m,revision=step1,","model_num_parameters"(...TRUNCATED) | 51a7ca9 | 1,723,751,353.851652 | "PyTorch version: 2.3.0+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to(...TRUNCATED) | 4.40.2 | null | {} | hf | EleutherAI/pythia-14m | EleutherAI__pythia-14m | 1,133,922.894151 | 1,134,001.333326 | 78.43917500483803 |
{"simple_cooccurrence_bias":{"likelihood_diff,none":-0.31463995695410724,"likelihood_diff_stderr,non(...TRUNCATED) | null | {
"simple_cooccurrence_bias": []
} | {"simple_cooccurrence_bias":{"task":"simple_cooccurrence_bias","group":["social_bias"],"dataset_path(...TRUNCATED) | {
"simple_cooccurrence_bias": 1
} | {
"simple_cooccurrence_bias": 0
} | {
"simple_cooccurrence_bias": {
"original": 351,
"effective": 351
}
} | {"model":"hf","model_args":"pretrained=EleutherAI/pythia-14m,revision=step1","model_num_parameters":(...TRUNCATED) | 51a7ca9 | 1,724,408,896.377194 | "PyTorch version: 2.4.0+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to(...TRUNCATED) | 4.44.0 | null | {} | hf | EleutherAI/pythia-14m | EleutherAI__pythia-14m | 4,697,261.07943 | 4,697,297.183277 | 36.10384631436318 |
{"blimp":{"acc,none":0.577134328358209,"acc_stderr,none":0.0016256946286422691,"alias":"blimp"},"bli(...TRUNCATED) | {
"blimp": {
"acc,none": 0.577134328358209,
"acc_stderr,none": 0.0016256946286422691,
"alias": "blimp"
}
} | {"blimp":["blimp_causative","blimp_determiner_noun_agreement_irregular_2","blimp_passive_1","blimp_w(...TRUNCATED) | {"blimp_adjunct_island":{"task":"blimp_adjunct_island","group":"blimp","dataset_path":"blimp","datas(...TRUNCATED) | {"blimp_adjunct_island":1.0,"blimp_anaphor_gender_agreement":1.0,"blimp_anaphor_number_agreement":1.(...TRUNCATED) | {"blimp":0,"blimp_adjunct_island":0,"blimp_anaphor_gender_agreement":0,"blimp_anaphor_number_agreeme(...TRUNCATED) | {"blimp_causative":{"original":1000,"effective":1000},"blimp_determiner_noun_agreement_irregular_2":(...TRUNCATED) | {"model":"hf","model_args":"pretrained=EleutherAI/pythia-14m,revision=step1000","model_num_parameter(...TRUNCATED) | 51a7ca9 | 1,720,432,542.210486 | "PyTorch version: 2.3.0+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to(...TRUNCATED) | 4.40.2 | null | {} | hf | EleutherAI/pythia-14m | EleutherAI__pythia-14m | 756,656.804734 | 756,983.172127 | 326.3673931409139 |
{"lambada_openai":{"perplexity,none":195988.90526637834,"perplexity_stderr,none":12193.7268807034,"a(...TRUNCATED) | null | {
"lambada_openai": []
} | {"lambada_openai":{"task":"lambada_openai","group":["lambada"],"dataset_path":"EleutherAI/lambada_op(...TRUNCATED) | {
"lambada_openai": 1
} | {
"lambada_openai": 0
} | {
"lambada_openai": {
"original": 5153,
"effective": 5153
}
} | {"model":"hf","model_args":"pretrained=EleutherAI/pythia-14m,revision=step1000,","model_num_paramete(...TRUNCATED) | 51a7ca9 | 1,723,752,224.187968 | "PyTorch version: 2.3.0+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to(...TRUNCATED) | 4.40.2 | null | {} | hf | EleutherAI/pythia-14m | EleutherAI__pythia-14m | 1,134,793.204587 | 1,134,878.555077 | 85.35048984992318 |
{"simple_cooccurrence_bias":{"likelihood_diff,none":0.48672151134867353,"likelihood_diff_stderr,none(...TRUNCATED) | null | {
"simple_cooccurrence_bias": []
} | {"simple_cooccurrence_bias":{"task":"simple_cooccurrence_bias","group":["social_bias"],"dataset_path(...TRUNCATED) | {
"simple_cooccurrence_bias": 1
} | {
"simple_cooccurrence_bias": 0
} | {
"simple_cooccurrence_bias": {
"original": 351,
"effective": 351
}
} | {"model":"hf","model_args":"pretrained=EleutherAI/pythia-14m,revision=step1000","model_num_parameter(...TRUNCATED) | 51a7ca9 | 1,724,409,271.13693 | "PyTorch version: 2.4.0+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to(...TRUNCATED) | 4.44.0 | null | {} | hf | EleutherAI/pythia-14m | EleutherAI__pythia-14m | 4,697,640.102159 | 4,697,671.799938 | 31.697778502479196 |
{"blimp":{"acc,none":0.6514925373134328,"acc_stderr,none":0.00155966533870429,"alias":"blimp"},"blim(...TRUNCATED) | {
"blimp": {
"acc,none": 0.6514925373134328,
"acc_stderr,none": 0.00155966533870429,
"alias": "blimp"
}
} | {"blimp":["blimp_causative","blimp_determiner_noun_agreement_irregular_2","blimp_passive_1","blimp_w(...TRUNCATED) | {"blimp_adjunct_island":{"task":"blimp_adjunct_island","group":"blimp","dataset_path":"blimp","datas(...TRUNCATED) | {"blimp_adjunct_island":1.0,"blimp_anaphor_gender_agreement":1.0,"blimp_anaphor_number_agreement":1.(...TRUNCATED) | {"blimp":0,"blimp_adjunct_island":0,"blimp_anaphor_gender_agreement":0,"blimp_anaphor_number_agreeme(...TRUNCATED) | {"blimp_causative":{"original":1000,"effective":1000},"blimp_determiner_noun_agreement_irregular_2":(...TRUNCATED) | {"model":"hf","model_args":"pretrained=EleutherAI/pythia-14m,revision=step10000","model_num_paramete(...TRUNCATED) | 51a7ca9 | 1,720,435,689.384633 | "PyTorch version: 2.3.0+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to(...TRUNCATED) | 4.40.2 | null | {} | hf | EleutherAI/pythia-14m | EleutherAI__pythia-14m | 759,789.583742 | 760,113.082642 | 323.4988997380715 |
End of preview.
No dataset card yet
- Downloads last month
- 0