open-r1-eval-leaderboard
/
eval_results
/teknium
/OpenHermes-2.5-Mistral-7B
/main
/mmlu
/results_2024-03-02T15-43-02.359297.json
| { | |
| "config_general": { | |
| "lighteval_sha": "?", | |
| "num_fewshot_seeds": 1, | |
| "override_batch_size": 1, | |
| "max_samples": null, | |
| "job_id": "", | |
| "start_time": 1752416.193571487, | |
| "end_time": 1753263.599800947, | |
| "total_evaluation_time_secondes": "847.4062294599134", | |
| "model_name": "teknium/OpenHermes-2.5-Mistral-7B", | |
| "model_sha": "24c0bea14d53e6f67f1fbe2eca5bfe7cae389b33", | |
| "model_dtype": "torch.bfloat16", | |
| "model_size": "13.99 GB", | |
| "config": null | |
| }, | |
| "results": { | |
| "lighteval|mmlu:abstract_algebra|5": { | |
| "acc": 0.34, | |
| "acc_stderr": 0.04760952285695235 | |
| }, | |
| "lighteval|mmlu:anatomy|5": { | |
| "acc": 0.6, | |
| "acc_stderr": 0.04232073695151589 | |
| }, | |
| "lighteval|mmlu:astronomy|5": { | |
| "acc": 0.6973684210526315, | |
| "acc_stderr": 0.037385206761196686 | |
| }, | |
| "lighteval|mmlu:business_ethics|5": { | |
| "acc": 0.63, | |
| "acc_stderr": 0.048523658709391 | |
| }, | |
| "lighteval|mmlu:clinical_knowledge|5": { | |
| "acc": 0.6754716981132075, | |
| "acc_stderr": 0.02881561571343211 | |
| }, | |
| "lighteval|mmlu:college_biology|5": { | |
| "acc": 0.7569444444444444, | |
| "acc_stderr": 0.0358687928008034 | |
| }, | |
| "lighteval|mmlu:college_chemistry|5": { | |
| "acc": 0.47, | |
| "acc_stderr": 0.050161355804659205 | |
| }, | |
| "lighteval|mmlu:college_computer_science|5": { | |
| "acc": 0.48, | |
| "acc_stderr": 0.050211673156867795 | |
| }, | |
| "lighteval|mmlu:college_mathematics|5": { | |
| "acc": 0.25, | |
| "acc_stderr": 0.04351941398892446 | |
| }, | |
| "lighteval|mmlu:college_medicine|5": { | |
| "acc": 0.6011560693641619, | |
| "acc_stderr": 0.037336266553835096 | |
| }, | |
| "lighteval|mmlu:college_physics|5": { | |
| "acc": 0.4019607843137255, | |
| "acc_stderr": 0.048786087144669955 | |
| }, | |
| "lighteval|mmlu:computer_security|5": { | |
| "acc": 0.79, | |
| "acc_stderr": 0.04093601807403326 | |
| }, | |
| "lighteval|mmlu:conceptual_physics|5": { | |
| "acc": 0.5531914893617021, | |
| "acc_stderr": 0.0325005368436584 | |
| }, | |
| "lighteval|mmlu:econometrics|5": { | |
| "acc": 0.49122807017543857, | |
| "acc_stderr": 0.04702880432049615 | |
| }, | |
| "lighteval|mmlu:electrical_engineering|5": { | |
| "acc": 0.5103448275862069, | |
| "acc_stderr": 0.04165774775728763 | |
| }, | |
| "lighteval|mmlu:elementary_mathematics|5": { | |
| "acc": 0.3994708994708995, | |
| "acc_stderr": 0.025225450284067884 | |
| }, | |
| "lighteval|mmlu:formal_logic|5": { | |
| "acc": 0.4126984126984127, | |
| "acc_stderr": 0.04403438954768176 | |
| }, | |
| "lighteval|mmlu:global_facts|5": { | |
| "acc": 0.38, | |
| "acc_stderr": 0.04878317312145633 | |
| }, | |
| "lighteval|mmlu:high_school_biology|5": { | |
| "acc": 0.7774193548387097, | |
| "acc_stderr": 0.023664216671642507 | |
| }, | |
| "lighteval|mmlu:high_school_chemistry|5": { | |
| "acc": 0.4827586206896552, | |
| "acc_stderr": 0.035158955511656986 | |
| }, | |
| "lighteval|mmlu:high_school_computer_science|5": { | |
| "acc": 0.67, | |
| "acc_stderr": 0.04725815626252607 | |
| }, | |
| "lighteval|mmlu:high_school_european_history|5": { | |
| "acc": 0.8181818181818182, | |
| "acc_stderr": 0.03011768892950357 | |
| }, | |
| "lighteval|mmlu:high_school_geography|5": { | |
| "acc": 0.7676767676767676, | |
| "acc_stderr": 0.030088629490217487 | |
| }, | |
| "lighteval|mmlu:high_school_government_and_politics|5": { | |
| "acc": 0.8652849740932642, | |
| "acc_stderr": 0.024639789097709443 | |
| }, | |
| "lighteval|mmlu:high_school_macroeconomics|5": { | |
| "acc": 0.617948717948718, | |
| "acc_stderr": 0.024635549163908237 | |
| }, | |
| "lighteval|mmlu:high_school_mathematics|5": { | |
| "acc": 0.3148148148148148, | |
| "acc_stderr": 0.028317533496066482 | |
| }, | |
| "lighteval|mmlu:high_school_microeconomics|5": { | |
| "acc": 0.6722689075630253, | |
| "acc_stderr": 0.030489911417673227 | |
| }, | |
| "lighteval|mmlu:high_school_physics|5": { | |
| "acc": 0.32450331125827814, | |
| "acc_stderr": 0.038227469376587525 | |
| }, | |
| "lighteval|mmlu:high_school_psychology|5": { | |
| "acc": 0.8256880733944955, | |
| "acc_stderr": 0.016265675632010333 | |
| }, | |
| "lighteval|mmlu:high_school_statistics|5": { | |
| "acc": 0.49074074074074076, | |
| "acc_stderr": 0.034093869469927006 | |
| }, | |
| "lighteval|mmlu:high_school_us_history|5": { | |
| "acc": 0.7892156862745098, | |
| "acc_stderr": 0.028626547912437406 | |
| }, | |
| "lighteval|mmlu:high_school_world_history|5": { | |
| "acc": 0.8016877637130801, | |
| "acc_stderr": 0.025955020841621115 | |
| }, | |
| "lighteval|mmlu:human_aging|5": { | |
| "acc": 0.6816143497757847, | |
| "acc_stderr": 0.03126580522513713 | |
| }, | |
| "lighteval|mmlu:human_sexuality|5": { | |
| "acc": 0.7633587786259542, | |
| "acc_stderr": 0.03727673575596914 | |
| }, | |
| "lighteval|mmlu:international_law|5": { | |
| "acc": 0.7933884297520661, | |
| "acc_stderr": 0.03695980128098824 | |
| }, | |
| "lighteval|mmlu:jurisprudence|5": { | |
| "acc": 0.7685185185185185, | |
| "acc_stderr": 0.04077494709252626 | |
| }, | |
| "lighteval|mmlu:logical_fallacies|5": { | |
| "acc": 0.7361963190184049, | |
| "acc_stderr": 0.03462419931615623 | |
| }, | |
| "lighteval|mmlu:machine_learning|5": { | |
| "acc": 0.5, | |
| "acc_stderr": 0.04745789978762494 | |
| }, | |
| "lighteval|mmlu:management|5": { | |
| "acc": 0.8058252427184466, | |
| "acc_stderr": 0.03916667762822584 | |
| }, | |
| "lighteval|mmlu:marketing|5": { | |
| "acc": 0.8760683760683761, | |
| "acc_stderr": 0.021586494001281382 | |
| }, | |
| "lighteval|mmlu:medical_genetics|5": { | |
| "acc": 0.65, | |
| "acc_stderr": 0.0479372485441102 | |
| }, | |
| "lighteval|mmlu:miscellaneous|5": { | |
| "acc": 0.8160919540229885, | |
| "acc_stderr": 0.013853724170922526 | |
| }, | |
| "lighteval|mmlu:moral_disputes|5": { | |
| "acc": 0.7225433526011561, | |
| "acc_stderr": 0.024105712607754307 | |
| }, | |
| "lighteval|mmlu:moral_scenarios|5": { | |
| "acc": 0.2916201117318436, | |
| "acc_stderr": 0.015201032512520429 | |
| }, | |
| "lighteval|mmlu:nutrition|5": { | |
| "acc": 0.7483660130718954, | |
| "acc_stderr": 0.024848018263875192 | |
| }, | |
| "lighteval|mmlu:philosophy|5": { | |
| "acc": 0.7041800643086816, | |
| "acc_stderr": 0.025922371788818767 | |
| }, | |
| "lighteval|mmlu:prehistory|5": { | |
| "acc": 0.7283950617283951, | |
| "acc_stderr": 0.024748624490537368 | |
| }, | |
| "lighteval|mmlu:professional_accounting|5": { | |
| "acc": 0.48226950354609927, | |
| "acc_stderr": 0.02980873964223777 | |
| }, | |
| "lighteval|mmlu:professional_law|5": { | |
| "acc": 0.4589308996088657, | |
| "acc_stderr": 0.012727084826799795 | |
| }, | |
| "lighteval|mmlu:professional_medicine|5": { | |
| "acc": 0.6544117647058824, | |
| "acc_stderr": 0.02888819310398863 | |
| }, | |
| "lighteval|mmlu:professional_psychology|5": { | |
| "acc": 0.6650326797385621, | |
| "acc_stderr": 0.019094228167000325 | |
| }, | |
| "lighteval|mmlu:public_relations|5": { | |
| "acc": 0.6454545454545455, | |
| "acc_stderr": 0.04582004841505417 | |
| }, | |
| "lighteval|mmlu:security_studies|5": { | |
| "acc": 0.7306122448979592, | |
| "acc_stderr": 0.02840125202902294 | |
| }, | |
| "lighteval|mmlu:sociology|5": { | |
| "acc": 0.8258706467661692, | |
| "acc_stderr": 0.026814951200421603 | |
| }, | |
| "lighteval|mmlu:us_foreign_policy|5": { | |
| "acc": 0.86, | |
| "acc_stderr": 0.0348735088019777 | |
| }, | |
| "lighteval|mmlu:virology|5": { | |
| "acc": 0.5301204819277109, | |
| "acc_stderr": 0.03885425420866767 | |
| }, | |
| "lighteval|mmlu:world_religions|5": { | |
| "acc": 0.8187134502923976, | |
| "acc_stderr": 0.029547741687640038 | |
| }, | |
| "lighteval|mmlu:_average|5": { | |
| "acc": 0.6300983764324458, | |
| "acc_stderr": 0.033838644880941675 | |
| } | |
| }, | |
| "versions": { | |
| "lighteval|mmlu:abstract_algebra|5": 0, | |
| "lighteval|mmlu:anatomy|5": 0, | |
| "lighteval|mmlu:astronomy|5": 0, | |
| "lighteval|mmlu:business_ethics|5": 0, | |
| "lighteval|mmlu:clinical_knowledge|5": 0, | |
| "lighteval|mmlu:college_biology|5": 0, | |
| "lighteval|mmlu:college_chemistry|5": 0, | |
| "lighteval|mmlu:college_computer_science|5": 0, | |
| "lighteval|mmlu:college_mathematics|5": 0, | |
| "lighteval|mmlu:college_medicine|5": 0, | |
| "lighteval|mmlu:college_physics|5": 0, | |
| "lighteval|mmlu:computer_security|5": 0, | |
| "lighteval|mmlu:conceptual_physics|5": 0, | |
| "lighteval|mmlu:econometrics|5": 0, | |
| "lighteval|mmlu:electrical_engineering|5": 0, | |
| "lighteval|mmlu:elementary_mathematics|5": 0, | |
| "lighteval|mmlu:formal_logic|5": 0, | |
| "lighteval|mmlu:global_facts|5": 0, | |
| "lighteval|mmlu:high_school_biology|5": 0, | |
| "lighteval|mmlu:high_school_chemistry|5": 0, | |
| "lighteval|mmlu:high_school_computer_science|5": 0, | |
| "lighteval|mmlu:high_school_european_history|5": 0, | |
| "lighteval|mmlu:high_school_geography|5": 0, | |
| "lighteval|mmlu:high_school_government_and_politics|5": 0, | |
| "lighteval|mmlu:high_school_macroeconomics|5": 0, | |
| "lighteval|mmlu:high_school_mathematics|5": 0, | |
| "lighteval|mmlu:high_school_microeconomics|5": 0, | |
| "lighteval|mmlu:high_school_physics|5": 0, | |
| "lighteval|mmlu:high_school_psychology|5": 0, | |
| "lighteval|mmlu:high_school_statistics|5": 0, | |
| "lighteval|mmlu:high_school_us_history|5": 0, | |
| "lighteval|mmlu:high_school_world_history|5": 0, | |
| "lighteval|mmlu:human_aging|5": 0, | |
| "lighteval|mmlu:human_sexuality|5": 0, | |
| "lighteval|mmlu:international_law|5": 0, | |
| "lighteval|mmlu:jurisprudence|5": 0, | |
| "lighteval|mmlu:logical_fallacies|5": 0, | |
| "lighteval|mmlu:machine_learning|5": 0, | |
| "lighteval|mmlu:management|5": 0, | |
| "lighteval|mmlu:marketing|5": 0, | |
| "lighteval|mmlu:medical_genetics|5": 0, | |
| "lighteval|mmlu:miscellaneous|5": 0, | |
| "lighteval|mmlu:moral_disputes|5": 0, | |
| "lighteval|mmlu:moral_scenarios|5": 0, | |
| "lighteval|mmlu:nutrition|5": 0, | |
| "lighteval|mmlu:philosophy|5": 0, | |
| "lighteval|mmlu:prehistory|5": 0, | |
| "lighteval|mmlu:professional_accounting|5": 0, | |
| "lighteval|mmlu:professional_law|5": 0, | |
| "lighteval|mmlu:professional_medicine|5": 0, | |
| "lighteval|mmlu:professional_psychology|5": 0, | |
| "lighteval|mmlu:public_relations|5": 0, | |
| "lighteval|mmlu:security_studies|5": 0, | |
| "lighteval|mmlu:sociology|5": 0, | |
| "lighteval|mmlu:us_foreign_policy|5": 0, | |
| "lighteval|mmlu:virology|5": 0, | |
| "lighteval|mmlu:world_religions|5": 0 | |
| }, | |
| "config_tasks": { | |
| "lighteval|mmlu:abstract_algebra": { | |
| "name": "mmlu:abstract_algebra", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "abstract_algebra", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 100, | |
| "effective_num_docs": 100 | |
| }, | |
| "lighteval|mmlu:anatomy": { | |
| "name": "mmlu:anatomy", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "anatomy", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 135, | |
| "effective_num_docs": 135 | |
| }, | |
| "lighteval|mmlu:astronomy": { | |
| "name": "mmlu:astronomy", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "astronomy", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 152, | |
| "effective_num_docs": 152 | |
| }, | |
| "lighteval|mmlu:business_ethics": { | |
| "name": "mmlu:business_ethics", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "business_ethics", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 100, | |
| "effective_num_docs": 100 | |
| }, | |
| "lighteval|mmlu:clinical_knowledge": { | |
| "name": "mmlu:clinical_knowledge", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "clinical_knowledge", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 265, | |
| "effective_num_docs": 265 | |
| }, | |
| "lighteval|mmlu:college_biology": { | |
| "name": "mmlu:college_biology", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "college_biology", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 144, | |
| "effective_num_docs": 144 | |
| }, | |
| "lighteval|mmlu:college_chemistry": { | |
| "name": "mmlu:college_chemistry", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "college_chemistry", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 100, | |
| "effective_num_docs": 100 | |
| }, | |
| "lighteval|mmlu:college_computer_science": { | |
| "name": "mmlu:college_computer_science", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "college_computer_science", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 100, | |
| "effective_num_docs": 100 | |
| }, | |
| "lighteval|mmlu:college_mathematics": { | |
| "name": "mmlu:college_mathematics", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "college_mathematics", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 100, | |
| "effective_num_docs": 100 | |
| }, | |
| "lighteval|mmlu:college_medicine": { | |
| "name": "mmlu:college_medicine", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "college_medicine", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 173, | |
| "effective_num_docs": 173 | |
| }, | |
| "lighteval|mmlu:college_physics": { | |
| "name": "mmlu:college_physics", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "college_physics", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 102, | |
| "effective_num_docs": 102 | |
| }, | |
| "lighteval|mmlu:computer_security": { | |
| "name": "mmlu:computer_security", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "computer_security", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 100, | |
| "effective_num_docs": 100 | |
| }, | |
| "lighteval|mmlu:conceptual_physics": { | |
| "name": "mmlu:conceptual_physics", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "conceptual_physics", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 235, | |
| "effective_num_docs": 235 | |
| }, | |
| "lighteval|mmlu:econometrics": { | |
| "name": "mmlu:econometrics", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "econometrics", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 114, | |
| "effective_num_docs": 114 | |
| }, | |
| "lighteval|mmlu:electrical_engineering": { | |
| "name": "mmlu:electrical_engineering", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "electrical_engineering", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 145, | |
| "effective_num_docs": 145 | |
| }, | |
| "lighteval|mmlu:elementary_mathematics": { | |
| "name": "mmlu:elementary_mathematics", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "elementary_mathematics", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 378, | |
| "effective_num_docs": 378 | |
| }, | |
| "lighteval|mmlu:formal_logic": { | |
| "name": "mmlu:formal_logic", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "formal_logic", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 126, | |
| "effective_num_docs": 126 | |
| }, | |
| "lighteval|mmlu:global_facts": { | |
| "name": "mmlu:global_facts", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "global_facts", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 100, | |
| "effective_num_docs": 100 | |
| }, | |
| "lighteval|mmlu:high_school_biology": { | |
| "name": "mmlu:high_school_biology", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "high_school_biology", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 310, | |
| "effective_num_docs": 310 | |
| }, | |
| "lighteval|mmlu:high_school_chemistry": { | |
| "name": "mmlu:high_school_chemistry", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "high_school_chemistry", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 203, | |
| "effective_num_docs": 203 | |
| }, | |
| "lighteval|mmlu:high_school_computer_science": { | |
| "name": "mmlu:high_school_computer_science", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "high_school_computer_science", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 100, | |
| "effective_num_docs": 100 | |
| }, | |
| "lighteval|mmlu:high_school_european_history": { | |
| "name": "mmlu:high_school_european_history", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "high_school_european_history", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 165, | |
| "effective_num_docs": 165 | |
| }, | |
| "lighteval|mmlu:high_school_geography": { | |
| "name": "mmlu:high_school_geography", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "high_school_geography", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 198, | |
| "effective_num_docs": 198 | |
| }, | |
| "lighteval|mmlu:high_school_government_and_politics": { | |
| "name": "mmlu:high_school_government_and_politics", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "high_school_government_and_politics", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 193, | |
| "effective_num_docs": 193 | |
| }, | |
| "lighteval|mmlu:high_school_macroeconomics": { | |
| "name": "mmlu:high_school_macroeconomics", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "high_school_macroeconomics", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 390, | |
| "effective_num_docs": 390 | |
| }, | |
| "lighteval|mmlu:high_school_mathematics": { | |
| "name": "mmlu:high_school_mathematics", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "high_school_mathematics", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 270, | |
| "effective_num_docs": 270 | |
| }, | |
| "lighteval|mmlu:high_school_microeconomics": { | |
| "name": "mmlu:high_school_microeconomics", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "high_school_microeconomics", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 238, | |
| "effective_num_docs": 238 | |
| }, | |
| "lighteval|mmlu:high_school_physics": { | |
| "name": "mmlu:high_school_physics", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "high_school_physics", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 151, | |
| "effective_num_docs": 151 | |
| }, | |
| "lighteval|mmlu:high_school_psychology": { | |
| "name": "mmlu:high_school_psychology", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "high_school_psychology", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 545, | |
| "effective_num_docs": 545 | |
| }, | |
| "lighteval|mmlu:high_school_statistics": { | |
| "name": "mmlu:high_school_statistics", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "high_school_statistics", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 216, | |
| "effective_num_docs": 216 | |
| }, | |
| "lighteval|mmlu:high_school_us_history": { | |
| "name": "mmlu:high_school_us_history", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "high_school_us_history", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 204, | |
| "effective_num_docs": 204 | |
| }, | |
| "lighteval|mmlu:high_school_world_history": { | |
| "name": "mmlu:high_school_world_history", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "high_school_world_history", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 237, | |
| "effective_num_docs": 237 | |
| }, | |
| "lighteval|mmlu:human_aging": { | |
| "name": "mmlu:human_aging", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "human_aging", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 223, | |
| "effective_num_docs": 223 | |
| }, | |
| "lighteval|mmlu:human_sexuality": { | |
| "name": "mmlu:human_sexuality", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "human_sexuality", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 131, | |
| "effective_num_docs": 131 | |
| }, | |
| "lighteval|mmlu:international_law": { | |
| "name": "mmlu:international_law", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "international_law", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 121, | |
| "effective_num_docs": 121 | |
| }, | |
| "lighteval|mmlu:jurisprudence": { | |
| "name": "mmlu:jurisprudence", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "jurisprudence", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 108, | |
| "effective_num_docs": 108 | |
| }, | |
| "lighteval|mmlu:logical_fallacies": { | |
| "name": "mmlu:logical_fallacies", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "logical_fallacies", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 163, | |
| "effective_num_docs": 163 | |
| }, | |
| "lighteval|mmlu:machine_learning": { | |
| "name": "mmlu:machine_learning", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "machine_learning", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 112, | |
| "effective_num_docs": 112 | |
| }, | |
| "lighteval|mmlu:management": { | |
| "name": "mmlu:management", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "management", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 103, | |
| "effective_num_docs": 103 | |
| }, | |
| "lighteval|mmlu:marketing": { | |
| "name": "mmlu:marketing", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "marketing", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 234, | |
| "effective_num_docs": 234 | |
| }, | |
| "lighteval|mmlu:medical_genetics": { | |
| "name": "mmlu:medical_genetics", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "medical_genetics", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 100, | |
| "effective_num_docs": 100 | |
| }, | |
| "lighteval|mmlu:miscellaneous": { | |
| "name": "mmlu:miscellaneous", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "miscellaneous", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 783, | |
| "effective_num_docs": 783 | |
| }, | |
| "lighteval|mmlu:moral_disputes": { | |
| "name": "mmlu:moral_disputes", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "moral_disputes", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 346, | |
| "effective_num_docs": 346 | |
| }, | |
| "lighteval|mmlu:moral_scenarios": { | |
| "name": "mmlu:moral_scenarios", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "moral_scenarios", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 895, | |
| "effective_num_docs": 895 | |
| }, | |
| "lighteval|mmlu:nutrition": { | |
| "name": "mmlu:nutrition", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "nutrition", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 306, | |
| "effective_num_docs": 306 | |
| }, | |
| "lighteval|mmlu:philosophy": { | |
| "name": "mmlu:philosophy", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "philosophy", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 311, | |
| "effective_num_docs": 311 | |
| }, | |
| "lighteval|mmlu:prehistory": { | |
| "name": "mmlu:prehistory", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "prehistory", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 324, | |
| "effective_num_docs": 324 | |
| }, | |
| "lighteval|mmlu:professional_accounting": { | |
| "name": "mmlu:professional_accounting", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "professional_accounting", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 282, | |
| "effective_num_docs": 282 | |
| }, | |
| "lighteval|mmlu:professional_law": { | |
| "name": "mmlu:professional_law", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "professional_law", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 1534, | |
| "effective_num_docs": 1534 | |
| }, | |
| "lighteval|mmlu:professional_medicine": { | |
| "name": "mmlu:professional_medicine", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "professional_medicine", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 272, | |
| "effective_num_docs": 272 | |
| }, | |
| "lighteval|mmlu:professional_psychology": { | |
| "name": "mmlu:professional_psychology", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "professional_psychology", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 612, | |
| "effective_num_docs": 612 | |
| }, | |
| "lighteval|mmlu:public_relations": { | |
| "name": "mmlu:public_relations", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "public_relations", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 110, | |
| "effective_num_docs": 110 | |
| }, | |
| "lighteval|mmlu:security_studies": { | |
| "name": "mmlu:security_studies", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "security_studies", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 245, | |
| "effective_num_docs": 245 | |
| }, | |
| "lighteval|mmlu:sociology": { | |
| "name": "mmlu:sociology", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "sociology", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 201, | |
| "effective_num_docs": 201 | |
| }, | |
| "lighteval|mmlu:us_foreign_policy": { | |
| "name": "mmlu:us_foreign_policy", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "us_foreign_policy", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 100, | |
| "effective_num_docs": 100 | |
| }, | |
| "lighteval|mmlu:virology": { | |
| "name": "mmlu:virology", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "virology", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 166, | |
| "effective_num_docs": 166 | |
| }, | |
| "lighteval|mmlu:world_religions": { | |
| "name": "mmlu:world_religions", | |
| "prompt_function": "mmlu_harness", | |
| "hf_repo": "lighteval/mmlu", | |
| "hf_subset": "world_religions", | |
| "metric": [ | |
| "loglikelihood_acc" | |
| ], | |
| "hf_avail_splits": [ | |
| "auxiliary_train", | |
| "test", | |
| "validation", | |
| "dev" | |
| ], | |
| "evaluation_splits": [ | |
| "test" | |
| ], | |
| "few_shots_split": "dev", | |
| "few_shots_select": "sequential", | |
| "generation_size": 1, | |
| "stop_sequence": [ | |
| "\n" | |
| ], | |
| "output_regex": null, | |
| "frozen": false, | |
| "suite": [ | |
| "lighteval", | |
| "mmlu" | |
| ], | |
| "original_num_docs": 171, | |
| "effective_num_docs": 171 | |
| } | |
| }, | |
| "summary_tasks": { | |
| "lighteval|mmlu:abstract_algebra|5": { | |
| "hashes": { | |
| "hash_examples": "4c76229e00c9c0e9", | |
| "hash_full_prompts": "a45d01c3409c889c", | |
| "hash_input_tokens": "6061ef74e94498a1", | |
| "hash_cont_tokens": "9e1c9ca2c51de57e" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 100, | |
| "padded": 400, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:anatomy|5": { | |
| "hashes": { | |
| "hash_examples": "6a1f8104dccbd33b", | |
| "hash_full_prompts": "e245c6600e03cc32", | |
| "hash_input_tokens": "1906e583b9621b5c", | |
| "hash_cont_tokens": "025910e68cf29c3d" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 135, | |
| "padded": 540, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:astronomy|5": { | |
| "hashes": { | |
| "hash_examples": "1302effa3a76ce4c", | |
| "hash_full_prompts": "390f9bddf857ad04", | |
| "hash_input_tokens": "771fefaee108888d", | |
| "hash_cont_tokens": "1a66fd04f03e0517" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 152, | |
| "padded": 608, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:business_ethics|5": { | |
| "hashes": { | |
| "hash_examples": "03cb8bce5336419a", | |
| "hash_full_prompts": "5504f893bc4f2fa1", | |
| "hash_input_tokens": "d94fae0608621dd6", | |
| "hash_cont_tokens": "9e1c9ca2c51de57e" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 100, | |
| "padded": 400, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:clinical_knowledge|5": { | |
| "hashes": { | |
| "hash_examples": "ffbb9c7b2be257f9", | |
| "hash_full_prompts": "106ad0bab4b90b78", | |
| "hash_input_tokens": "e8436d40a9c05ea3", | |
| "hash_cont_tokens": "de872053260a1588" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 265, | |
| "padded": 1060, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:college_biology|5": { | |
| "hashes": { | |
| "hash_examples": "3ee77f176f38eb8e", | |
| "hash_full_prompts": "59f9bdf2695cb226", | |
| "hash_input_tokens": "1bc1db858463d32a", | |
| "hash_cont_tokens": "9ace296b3e00bba3" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 144, | |
| "padded": 576, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:college_chemistry|5": { | |
| "hashes": { | |
| "hash_examples": "ce61a69c46d47aeb", | |
| "hash_full_prompts": "3cac9b759fcff7a0", | |
| "hash_input_tokens": "2a3c52842d61ce67", | |
| "hash_cont_tokens": "9e1c9ca2c51de57e" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 100, | |
| "padded": 400, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:college_computer_science|5": { | |
| "hashes": { | |
| "hash_examples": "32805b52d7d5daab", | |
| "hash_full_prompts": "010b0cca35070130", | |
| "hash_input_tokens": "a6a78a8854b3ff3c", | |
| "hash_cont_tokens": "9e1c9ca2c51de57e" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 100, | |
| "padded": 400, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:college_mathematics|5": { | |
| "hashes": { | |
| "hash_examples": "55da1a0a0bd33722", | |
| "hash_full_prompts": "511422eb9eefc773", | |
| "hash_input_tokens": "9067af15a43e3943", | |
| "hash_cont_tokens": "9e1c9ca2c51de57e" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 100, | |
| "padded": 400, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:college_medicine|5": { | |
| "hashes": { | |
| "hash_examples": "c33e143163049176", | |
| "hash_full_prompts": "c8cc1a82a51a046e", | |
| "hash_input_tokens": "d4973e45d254d606", | |
| "hash_cont_tokens": "c80c0b5489bdbc5a" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 173, | |
| "padded": 692, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:college_physics|5": { | |
| "hashes": { | |
| "hash_examples": "ebdab1cdb7e555df", | |
| "hash_full_prompts": "e40721b5059c5818", | |
| "hash_input_tokens": "974434dd212cc64c", | |
| "hash_cont_tokens": "569fcb9ac44734ae" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 102, | |
| "padded": 408, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:computer_security|5": { | |
| "hashes": { | |
| "hash_examples": "a24fd7d08a560921", | |
| "hash_full_prompts": "946c9be5964ac44a", | |
| "hash_input_tokens": "03a6468f366cc5c9", | |
| "hash_cont_tokens": "9e1c9ca2c51de57e" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 100, | |
| "padded": 400, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:conceptual_physics|5": { | |
| "hashes": { | |
| "hash_examples": "8300977a79386993", | |
| "hash_full_prompts": "506a4f6094cc40c9", | |
| "hash_input_tokens": "f534b68e21be3b1a", | |
| "hash_cont_tokens": "6e88c64c1a76752a" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 235, | |
| "padded": 940, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:econometrics|5": { | |
| "hashes": { | |
| "hash_examples": "ddde36788a04a46f", | |
| "hash_full_prompts": "4ed2703f27f1ed05", | |
| "hash_input_tokens": "8ff52a6059f5bdd9", | |
| "hash_cont_tokens": "a315e0e16c922c3c" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 114, | |
| "padded": 456, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:electrical_engineering|5": { | |
| "hashes": { | |
| "hash_examples": "acbc5def98c19b3f", | |
| "hash_full_prompts": "d8f4b3e11c23653c", | |
| "hash_input_tokens": "c33c375027d89492", | |
| "hash_cont_tokens": "44c72e6a7422c304" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 145, | |
| "padded": 580, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:elementary_mathematics|5": { | |
| "hashes": { | |
| "hash_examples": "146e61d07497a9bd", | |
| "hash_full_prompts": "256d111bd15647ff", | |
| "hash_input_tokens": "2ef5113cea686f48", | |
| "hash_cont_tokens": "cac0a6c304791bb7" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 378, | |
| "padded": 1512, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:formal_logic|5": { | |
| "hashes": { | |
| "hash_examples": "8635216e1909a03f", | |
| "hash_full_prompts": "1171d04f3b1a11f5", | |
| "hash_input_tokens": "ec97e1c379123fff", | |
| "hash_cont_tokens": "8801fad3bbc72e57" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 126, | |
| "padded": 504, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:global_facts|5": { | |
| "hashes": { | |
| "hash_examples": "30b315aa6353ee47", | |
| "hash_full_prompts": "a7e56dbc074c7529", | |
| "hash_input_tokens": "2b0807209002d279", | |
| "hash_cont_tokens": "9e1c9ca2c51de57e" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 100, | |
| "padded": 400, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:high_school_biology|5": { | |
| "hashes": { | |
| "hash_examples": "c9136373af2180de", | |
| "hash_full_prompts": "ad6e859ed978e04a", | |
| "hash_input_tokens": "e8cadacc947daa13", | |
| "hash_cont_tokens": "2d57d9e2c5a1fd64" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 310, | |
| "padded": 1240, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:high_school_chemistry|5": { | |
| "hashes": { | |
| "hash_examples": "b0661bfa1add6404", | |
| "hash_full_prompts": "6eb9c04bcc8a8f2a", | |
| "hash_input_tokens": "8ae6b3d5212ac67f", | |
| "hash_cont_tokens": "bb0fd92673ddfb31" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 203, | |
| "padded": 812, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:high_school_computer_science|5": { | |
| "hashes": { | |
| "hash_examples": "80fc1d623a3d665f", | |
| "hash_full_prompts": "8e51bc91c81cf8dd", | |
| "hash_input_tokens": "46dfdc239de27d6e", | |
| "hash_cont_tokens": "9e1c9ca2c51de57e" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 100, | |
| "padded": 400, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:high_school_european_history|5": { | |
| "hashes": { | |
| "hash_examples": "854da6e5af0fe1a1", | |
| "hash_full_prompts": "664a1f16c9f3195c", | |
| "hash_input_tokens": "a3c136d3ff165617", | |
| "hash_cont_tokens": "16e494cddccc4a04" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 165, | |
| "padded": 656, | |
| "non_padded": 4, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:high_school_geography|5": { | |
| "hashes": { | |
| "hash_examples": "7dc963c7acd19ad8", | |
| "hash_full_prompts": "f3acf911f4023c8a", | |
| "hash_input_tokens": "e1360551f2ad3e47", | |
| "hash_cont_tokens": "16b7f65a07b3d47b" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 198, | |
| "padded": 792, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:high_school_government_and_politics|5": { | |
| "hashes": { | |
| "hash_examples": "1f675dcdebc9758f", | |
| "hash_full_prompts": "066254feaa3158ae", | |
| "hash_input_tokens": "6564364e1f4d4c79", | |
| "hash_cont_tokens": "476e87fd675136aa" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 193, | |
| "padded": 772, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:high_school_macroeconomics|5": { | |
| "hashes": { | |
| "hash_examples": "2fb32cf2d80f0b35", | |
| "hash_full_prompts": "19a7fa502aa85c95", | |
| "hash_input_tokens": "d59bdfdf903bf379", | |
| "hash_cont_tokens": "b0c7b4c5f7bdf3e7" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 390, | |
| "padded": 1560, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:high_school_mathematics|5": { | |
| "hashes": { | |
| "hash_examples": "fd6646fdb5d58a1f", | |
| "hash_full_prompts": "4f704e369778b5b0", | |
| "hash_input_tokens": "b3a5c15701024f1f", | |
| "hash_cont_tokens": "1a05d6ff49846fd1" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 270, | |
| "padded": 1080, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:high_school_microeconomics|5": { | |
| "hashes": { | |
| "hash_examples": "2118f21f71d87d84", | |
| "hash_full_prompts": "4350f9e2240f8010", | |
| "hash_input_tokens": "69e3156cb9bbbda9", | |
| "hash_cont_tokens": "0e7f0645ffffd6cd" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 238, | |
| "padded": 949, | |
| "non_padded": 3, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:high_school_physics|5": { | |
| "hashes": { | |
| "hash_examples": "dc3ce06378548565", | |
| "hash_full_prompts": "5dc0d6831b66188f", | |
| "hash_input_tokens": "ba950d9d4f5d5e47", | |
| "hash_cont_tokens": "41ca6560b8c10183" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 151, | |
| "padded": 604, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:high_school_psychology|5": { | |
| "hashes": { | |
| "hash_examples": "c8d1d98a40e11f2f", | |
| "hash_full_prompts": "af2b097da6d50365", | |
| "hash_input_tokens": "a54adefaeb5500a2", | |
| "hash_cont_tokens": "53a17ff85c607844" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 545, | |
| "padded": 2178, | |
| "non_padded": 2, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:high_school_statistics|5": { | |
| "hashes": { | |
| "hash_examples": "666c8759b98ee4ff", | |
| "hash_full_prompts": "c757694421d6d68d", | |
| "hash_input_tokens": "240419bd9137ca86", | |
| "hash_cont_tokens": "bc9063ad140cc941" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 216, | |
| "padded": 864, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:high_school_us_history|5": { | |
| "hashes": { | |
| "hash_examples": "95fef1c4b7d3f81e", | |
| "hash_full_prompts": "e34a028d0ddeec5e", | |
| "hash_input_tokens": "b27e2d090c7722d6", | |
| "hash_cont_tokens": "5cf777085ba01096" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 204, | |
| "padded": 816, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:high_school_world_history|5": { | |
| "hashes": { | |
| "hash_examples": "7e5085b6184b0322", | |
| "hash_full_prompts": "1fa3d51392765601", | |
| "hash_input_tokens": "a0503454c72d62f4", | |
| "hash_cont_tokens": "152af2d9e4830517" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 237, | |
| "padded": 948, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:human_aging|5": { | |
| "hashes": { | |
| "hash_examples": "c17333e7c7c10797", | |
| "hash_full_prompts": "cac900721f9a1a94", | |
| "hash_input_tokens": "cb1a5f4e8d8ece53", | |
| "hash_cont_tokens": "da4d9eaa044021dd" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 223, | |
| "padded": 892, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:human_sexuality|5": { | |
| "hashes": { | |
| "hash_examples": "4edd1e9045df5e3d", | |
| "hash_full_prompts": "0d6567bafee0a13c", | |
| "hash_input_tokens": "06f0a1b69fc0f6e9", | |
| "hash_cont_tokens": "1b99e384258a4eeb" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 131, | |
| "padded": 524, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:international_law|5": { | |
| "hashes": { | |
| "hash_examples": "db2fa00d771a062a", | |
| "hash_full_prompts": "d018f9116479795e", | |
| "hash_input_tokens": "24cda8ff066603d5", | |
| "hash_cont_tokens": "cbf02c30cdded208" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 121, | |
| "padded": 484, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:jurisprudence|5": { | |
| "hashes": { | |
| "hash_examples": "e956f86b124076fe", | |
| "hash_full_prompts": "1487e89a10ec58b7", | |
| "hash_input_tokens": "6a574eda8bdea629", | |
| "hash_cont_tokens": "4b248cf879d97a50" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 108, | |
| "padded": 424, | |
| "non_padded": 8, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:logical_fallacies|5": { | |
| "hashes": { | |
| "hash_examples": "956e0e6365ab79f1", | |
| "hash_full_prompts": "677785b2181f9243", | |
| "hash_input_tokens": "79da057bb404ffdd", | |
| "hash_cont_tokens": "6d9c35172b158838" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 163, | |
| "padded": 632, | |
| "non_padded": 20, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:machine_learning|5": { | |
| "hashes": { | |
| "hash_examples": "397997cc6f4d581e", | |
| "hash_full_prompts": "769ee14a2aea49bb", | |
| "hash_input_tokens": "1368f69e651d7a49", | |
| "hash_cont_tokens": "66c3ec85fee2fc98" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 112, | |
| "padded": 448, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:management|5": { | |
| "hashes": { | |
| "hash_examples": "2bcbe6f6ca63d740", | |
| "hash_full_prompts": "cb1ff9dac9582144", | |
| "hash_input_tokens": "4932314520ff5a1c", | |
| "hash_cont_tokens": "5e2470abd1fb9d10" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 103, | |
| "padded": 412, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:marketing|5": { | |
| "hashes": { | |
| "hash_examples": "8ddb20d964a1b065", | |
| "hash_full_prompts": "9fc2114a187ad9a2", | |
| "hash_input_tokens": "c566f215df327b23", | |
| "hash_cont_tokens": "27fe68d9630f8999" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 234, | |
| "padded": 916, | |
| "non_padded": 20, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:medical_genetics|5": { | |
| "hashes": { | |
| "hash_examples": "182a71f4763d2cea", | |
| "hash_full_prompts": "46a616fa51878959", | |
| "hash_input_tokens": "2d52eb85effca1ce", | |
| "hash_cont_tokens": "9e1c9ca2c51de57e" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 100, | |
| "padded": 400, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:miscellaneous|5": { | |
| "hashes": { | |
| "hash_examples": "4c404fdbb4ca57fc", | |
| "hash_full_prompts": "0813e1be36dbaae1", | |
| "hash_input_tokens": "8ab40049dc296984", | |
| "hash_cont_tokens": "dfa423a160edd337" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 783, | |
| "padded": 3128, | |
| "non_padded": 4, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:moral_disputes|5": { | |
| "hashes": { | |
| "hash_examples": "60cbd2baa3fea5c9", | |
| "hash_full_prompts": "1d14adebb9b62519", | |
| "hash_input_tokens": "4c5f82d25a8ebf96", | |
| "hash_cont_tokens": "bef966e6669349be" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 346, | |
| "padded": 1380, | |
| "non_padded": 4, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:moral_scenarios|5": { | |
| "hashes": { | |
| "hash_examples": "fd8b0431fbdd75ef", | |
| "hash_full_prompts": "b80d3d236165e3de", | |
| "hash_input_tokens": "72d00d71f8182e56", | |
| "hash_cont_tokens": "a7bfdd944d86bcb5" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 895, | |
| "padded": 3575, | |
| "non_padded": 5, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:nutrition|5": { | |
| "hashes": { | |
| "hash_examples": "71e55e2b829b6528", | |
| "hash_full_prompts": "2bfb18e5fab8dea7", | |
| "hash_input_tokens": "1c01b894ae13a2f4", | |
| "hash_cont_tokens": "fcda7736026f2449" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 306, | |
| "padded": 1224, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:philosophy|5": { | |
| "hashes": { | |
| "hash_examples": "a6d489a8d208fa4b", | |
| "hash_full_prompts": "e8c0d5b6dae3ccc8", | |
| "hash_input_tokens": "344b97bbc55eadeb", | |
| "hash_cont_tokens": "0f39b851342e8986" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 311, | |
| "padded": 1244, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:prehistory|5": { | |
| "hashes": { | |
| "hash_examples": "6cc50f032a19acaa", | |
| "hash_full_prompts": "4a6a1d3ab1bf28e4", | |
| "hash_input_tokens": "e2270c2e739d565b", | |
| "hash_cont_tokens": "b60e45d3e9856b35" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 324, | |
| "padded": 1280, | |
| "non_padded": 16, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:professional_accounting|5": { | |
| "hashes": { | |
| "hash_examples": "50f57ab32f5f6cea", | |
| "hash_full_prompts": "e60129bd2d82ffc6", | |
| "hash_input_tokens": "b6e8898d96ed525d", | |
| "hash_cont_tokens": "a0c4e121b7293818" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 282, | |
| "padded": 1112, | |
| "non_padded": 16, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:professional_law|5": { | |
| "hashes": { | |
| "hash_examples": "a8fdc85c64f4b215", | |
| "hash_full_prompts": "0dbb1d9b72dcea03", | |
| "hash_input_tokens": "71053a5cb26234dc", | |
| "hash_cont_tokens": "68b662abeba54fbc" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 1534, | |
| "padded": 6136, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:professional_medicine|5": { | |
| "hashes": { | |
| "hash_examples": "c373a28a3050a73a", | |
| "hash_full_prompts": "5e040f9ca68b089e", | |
| "hash_input_tokens": "b43ad52177e11456", | |
| "hash_cont_tokens": "6caeac5412bb4a09" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 272, | |
| "padded": 1088, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:professional_psychology|5": { | |
| "hashes": { | |
| "hash_examples": "bf5254fe818356af", | |
| "hash_full_prompts": "b386ecda8b87150e", | |
| "hash_input_tokens": "c250d3866bd3c8d8", | |
| "hash_cont_tokens": "79b091252a1095a9" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 612, | |
| "padded": 2448, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:public_relations|5": { | |
| "hashes": { | |
| "hash_examples": "b66d52e28e7d14e0", | |
| "hash_full_prompts": "fe43562263e25677", | |
| "hash_input_tokens": "d4b9f802b45946f8", | |
| "hash_cont_tokens": "987115a77c8704f0" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 110, | |
| "padded": 436, | |
| "non_padded": 4, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:security_studies|5": { | |
| "hashes": { | |
| "hash_examples": "514c14feaf000ad9", | |
| "hash_full_prompts": "27d4a2ac541ef4b9", | |
| "hash_input_tokens": "dd7c51a906f3bf73", | |
| "hash_cont_tokens": "6c35bc7e96074b27" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 245, | |
| "padded": 980, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:sociology|5": { | |
| "hashes": { | |
| "hash_examples": "f6c9bc9d18c80870", | |
| "hash_full_prompts": "c072ea7d1a1524f2", | |
| "hash_input_tokens": "50d0b11b96edc318", | |
| "hash_cont_tokens": "32af622f73b2e657" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 201, | |
| "padded": 804, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:us_foreign_policy|5": { | |
| "hashes": { | |
| "hash_examples": "ed7b78629db6678f", | |
| "hash_full_prompts": "341a97ca3e4d699d", | |
| "hash_input_tokens": "f16b53370750082e", | |
| "hash_cont_tokens": "9e1c9ca2c51de57e" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 100, | |
| "padded": 400, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:virology|5": { | |
| "hashes": { | |
| "hash_examples": "bc52ffdc3f9b994a", | |
| "hash_full_prompts": "651d471e2eb8b5e9", | |
| "hash_input_tokens": "61ad3b476830b6f3", | |
| "hash_cont_tokens": "beded8c3660dc8f5" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 166, | |
| "padded": 664, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| }, | |
| "lighteval|mmlu:world_religions|5": { | |
| "hashes": { | |
| "hash_examples": "ecdb4a4f94f62930", | |
| "hash_full_prompts": "3773f03542ce44a3", | |
| "hash_input_tokens": "804fecc55001e28a", | |
| "hash_cont_tokens": "9b1952a4af3d6a73" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 171, | |
| "padded": 684, | |
| "non_padded": 0, | |
| "effective_few_shots": 5.0, | |
| "num_truncated_few_shots": 0 | |
| } | |
| }, | |
| "summary_general": { | |
| "hashes": { | |
| "hash_examples": "341a076d0beb7048", | |
| "hash_full_prompts": "a5c8f2b7ff4f5ae2", | |
| "hash_input_tokens": "9273ebae51e8421d", | |
| "hash_cont_tokens": "25e9f343d6b95644" | |
| }, | |
| "truncated": 0, | |
| "non_truncated": 14042, | |
| "padded": 56062, | |
| "non_padded": 106, | |
| "num_truncated_few_shots": 0 | |
| } | |
| } |