datapack updates

lm-eval-output/rwkv-x-dev/R4-1B5-With-Mask/pythia/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0d060507c1028d5988048b82d93480f5b4107ce93d813c29dd07707bf36596cd
+size 407135

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/ai2_arc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,132 @@
+{
+  "results": {
+    "ai2_arc": {
+      "acc,none": 0.6169673055242391,
+      "acc_stderr,none": 0.10976273750365907,
+      "acc_norm,none": 0.6073844419391207,
+      "acc_norm_stderr,none": 0.09214502715899463,
+      "alias": "ai2_arc"
+    },
+    "arc_challenge": {
+      "acc,none": 0.3848122866894198,
+      "acc_stderr,none": 0.014218371065251104,
+      "acc_norm,none": 0.4129692832764505,
+      "acc_norm_stderr,none": 0.014388344935398326,
+      "alias": " - arc_challenge"
+    },
+    "arc_easy": {
+      "acc,none": 0.7314814814814815,
+      "acc_stderr,none": 0.009094042554994854,
+      "acc_norm,none": 0.7032828282828283,
+      "acc_norm_stderr,none": 0.009373559492986853,
+      "alias": " - arc_easy"
+    }
+  },
+  "groups": {
+    "ai2_arc": {
+      "acc,none": 0.6169673055242391,
+      "acc_stderr,none": 0.10976273750365907,
+      "acc_norm,none": 0.6073844419391207,
+      "acc_norm_stderr,none": 0.09214502715899463,
+      "alias": "ai2_arc"
+    }
+  },
+  "configs": {
+    "arc_challenge": {
+      "task": "arc_challenge",
+      "group": [
+        "ai2_arc"
+      ],
+      "dataset_path": "allenai/ai2_arc",
+      "dataset_name": "ARC-Challenge",
+      "training_split": "train",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "Question: {{question}}\nAnswer:",
+      "doc_to_target": "{{choices.label.index(answerKey)}}",
+      "doc_to_choice": "{{choices.text}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "acc_norm",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": true,
+      "doc_to_decontamination_query": "Question: {{question}}\nAnswer:",
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "arc_easy": {
+      "task": "arc_easy",
+      "group": [
+        "ai2_arc"
+      ],
+      "dataset_path": "allenai/ai2_arc",
+      "dataset_name": "ARC-Easy",
+      "training_split": "train",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "Question: {{question}}\nAnswer:",
+      "doc_to_target": "{{choices.label.index(answerKey)}}",
+      "doc_to_choice": "{{choices.text}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "acc_norm",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": true,
+      "doc_to_decontamination_query": "Question: {{question}}\nAnswer:",
+      "metadata": {
+        "version": 1.0
+      }
+    }
+  },
+  "versions": {
+    "ai2_arc": "N/A",
+    "arc_challenge": 1.0,
+    "arc_easy": 1.0
+  },
+  "n-shot": {
+    "ai2_arc": 0,
+    "arc_challenge": 0,
+    "arc_easy": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/R4-7B-15t-No-Mask_pth,dtype=bfloat16,trust_remote_code=True",
+    "batch_size": "auto",
+    "batch_sizes": [
+      64
+    ],
+    "device": null,
+    "use_cache": null,
+    "limit": null,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": null
+  },
+  "git_hash": "8281e96"
+}

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/ai2_arc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7c1a773212ab17a1eedeb744cc0df9fddb28e91d40d95ff63dda014d8710d9ac
+size 48084

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/anli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,161 @@
+{
+  "results": {
+    "anli": {
+      "acc,none": 0.36125,
+      "acc_stderr,none": 0.014724861303290397,
+      "alias": "anli"
+    },
+    "anli_r1": {
+      "acc,none": 0.36,
+      "acc_stderr,none": 0.015186527932040127,
+      "alias": " - anli_r1"
+    },
+    "anli_r2": {
+      "acc,none": 0.361,
+      "acc_stderr,none": 0.015195720118175115,
+      "alias": " - anli_r2"
+    },
+    "anli_r3": {
+      "acc,none": 0.3625,
+      "acc_stderr,none": 0.013883037874225516,
+      "alias": " - anli_r3"
+    }
+  },
+  "groups": {
+    "anli": {
+      "acc,none": 0.36125,
+      "acc_stderr,none": 0.014724861303290397,
+      "alias": "anli"
+    }
+  },
+  "configs": {
+    "anli_r1": {
+      "task": "anli_r1",
+      "group": [
+        "anli"
+      ],
+      "dataset_path": "anli",
+      "training_split": "train_r1",
+      "validation_split": "dev_r1",
+      "test_split": "test_r1",
+      "doc_to_text": "{{premise}}\nQuestion: {{hypothesis}} True, False, or Neither?\nAnswer:",
+      "doc_to_target": "{{['True', 'Neither', 'False'][label]}}",
+      "doc_to_choice": [
+        "True",
+        "Neither",
+        "False"
+      ],
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": true,
+      "doc_to_decontamination_query": "premise",
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "anli_r2": {
+      "task": "anli_r2",
+      "group": [
+        "anli"
+      ],
+      "dataset_path": "anli",
+      "training_split": "train_r2",
+      "validation_split": "dev_r2",
+      "test_split": "test_r2",
+      "doc_to_text": "{{premise}}\nQuestion: {{hypothesis}} True, False, or Neither?\nAnswer:",
+      "doc_to_target": "{{['True', 'Neither', 'False'][label]}}",
+      "doc_to_choice": [
+        "True",
+        "Neither",
+        "False"
+      ],
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": true,
+      "doc_to_decontamination_query": "premise",
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "anli_r3": {
+      "task": "anli_r3",
+      "group": [
+        "anli"
+      ],
+      "dataset_path": "anli",
+      "training_split": "train_r3",
+      "validation_split": "dev_r3",
+      "test_split": "test_r3",
+      "doc_to_text": "{{premise}}\nQuestion: {{hypothesis}} True, False, or Neither?\nAnswer:",
+      "doc_to_target": "{{['True', 'Neither', 'False'][label]}}",
+      "doc_to_choice": [
+        "True",
+        "Neither",
+        "False"
+      ],
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": true,
+      "doc_to_decontamination_query": "premise",
+      "metadata": {
+        "version": 1.0
+      }
+    }
+  },
+  "versions": {
+    "anli": "N/A",
+    "anli_r1": 1.0,
+    "anli_r2": 1.0,
+    "anli_r3": 1.0
+  },
+  "n-shot": {
+    "anli": 0,
+    "anli_r1": 0,
+    "anli_r2": 0,
+    "anli_r3": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/R4-7B-15t-No-Mask_pth,dtype=bfloat16,trust_remote_code=True",
+    "batch_size": "auto",
+    "batch_sizes": [
+      64
+    ],
+    "device": null,
+    "use_cache": null,
+    "limit": null,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": null
+  },
+  "git_hash": "8281e96"
+}

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/anli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c6fe8e5ae65dd7cb1ae0ad057e1c1ffab76cb0846c146bec8e6db4ad60327971
+size 47935

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/blimp/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,2249 @@
+{
+  "results": {
+    "blimp": {
+      "acc,none": 0.8223731343283582,
+      "acc_stderr,none": 0.16119006470239358,
+      "alias": "blimp"
+    },
+    "blimp_adjunct_island": {
+      "acc,none": 0.906,
+      "acc_stderr,none": 0.009233052000787735,
+      "alias": " - blimp_adjunct_island"
+    },
+    "blimp_anaphor_gender_agreement": {
+      "acc,none": 0.989,
+      "acc_stderr,none": 0.0032999833166078166,
+      "alias": " - blimp_anaphor_gender_agreement"
+    },
+    "blimp_anaphor_number_agreement": {
+      "acc,none": 0.998,
+      "acc_stderr,none": 0.0014135055705577929,
+      "alias": " - blimp_anaphor_number_agreement"
+    },
+    "blimp_animate_subject_passive": {
+      "acc,none": 0.829,
+      "acc_stderr,none": 0.0119122164562646,
+      "alias": " - blimp_animate_subject_passive"
+    },
+    "blimp_animate_subject_trans": {
+      "acc,none": 0.894,
+      "acc_stderr,none": 0.009739551265785136,
+      "alias": " - blimp_animate_subject_trans"
+    },
+    "blimp_causative": {
+      "acc,none": 0.75,
+      "acc_stderr,none": 0.013699915608779773,
+      "alias": " - blimp_causative"
+    },
+    "blimp_complex_NP_island": {
+      "acc,none": 0.58,
+      "acc_stderr,none": 0.015615500115072956,
+      "alias": " - blimp_complex_NP_island"
+    },
+    "blimp_coordinate_structure_constraint_complex_left_branch": {
+      "acc,none": 0.798,
+      "acc_stderr,none": 0.012702651587655147,
+      "alias": " - blimp_coordinate_structure_constraint_complex_left_branch"
+    },
+    "blimp_coordinate_structure_constraint_object_extraction": {
+      "acc,none": 0.87,
+      "acc_stderr,none": 0.01064016979249935,
+      "alias": " - blimp_coordinate_structure_constraint_object_extraction"
+    },
+    "blimp_determiner_noun_agreement_1": {
+      "acc,none": 0.996,
+      "acc_stderr,none": 0.001996994739098728,
+      "alias": " - blimp_determiner_noun_agreement_1"
+    },
+    "blimp_determiner_noun_agreement_2": {
+      "acc,none": 0.988,
+      "acc_stderr,none": 0.0034449771940998617,
+      "alias": " - blimp_determiner_noun_agreement_2"
+    },
+    "blimp_determiner_noun_agreement_irregular_1": {
+      "acc,none": 0.962,
+      "acc_stderr,none": 0.006049181150584948,
+      "alias": " - blimp_determiner_noun_agreement_irregular_1"
+    },
+    "blimp_determiner_noun_agreement_irregular_2": {
+      "acc,none": 0.953,
+      "acc_stderr,none": 0.006695956678163041,
+      "alias": " - blimp_determiner_noun_agreement_irregular_2"
+    },
+    "blimp_determiner_noun_agreement_with_adj_2": {
+      "acc,none": 0.96,
+      "acc_stderr,none": 0.0061998740663370775,
+      "alias": " - blimp_determiner_noun_agreement_with_adj_2"
+    },
+    "blimp_determiner_noun_agreement_with_adj_irregular_1": {
+      "acc,none": 0.927,
+      "acc_stderr,none": 0.008230354715244057,
+      "alias": " - blimp_determiner_noun_agreement_with_adj_irregular_1"
+    },
+    "blimp_determiner_noun_agreement_with_adj_irregular_2": {
+      "acc,none": 0.932,
+      "acc_stderr,none": 0.007964887911291603,
+      "alias": " - blimp_determiner_noun_agreement_with_adj_irregular_2"
+    },
+    "blimp_determiner_noun_agreement_with_adjective_1": {
+      "acc,none": 0.982,
+      "acc_stderr,none": 0.004206387249611444,
+      "alias": " - blimp_determiner_noun_agreement_with_adjective_1"
+    },
+    "blimp_distractor_agreement_relational_noun": {
+      "acc,none": 0.893,
+      "acc_stderr,none": 0.009779910359847165,
+      "alias": " - blimp_distractor_agreement_relational_noun"
+    },
+    "blimp_distractor_agreement_relative_clause": {
+      "acc,none": 0.717,
+      "acc_stderr,none": 0.014251810906481735,
+      "alias": " - blimp_distractor_agreement_relative_clause"
+    },
+    "blimp_drop_argument": {
+      "acc,none": 0.747,
+      "acc_stderr,none": 0.01375427861358708,
+      "alias": " - blimp_drop_argument"
+    },
+    "blimp_ellipsis_n_bar_1": {
+      "acc,none": 0.768,
+      "acc_stderr,none": 0.01335493745228157,
+      "alias": " - blimp_ellipsis_n_bar_1"
+    },
+    "blimp_ellipsis_n_bar_2": {
+      "acc,none": 0.939,
+      "acc_stderr,none": 0.007572076091557418,
+      "alias": " - blimp_ellipsis_n_bar_2"
+    },
+    "blimp_existential_there_object_raising": {
+      "acc,none": 0.858,
+      "acc_stderr,none": 0.011043457699378234,
+      "alias": " - blimp_existential_there_object_raising"
+    },
+    "blimp_existential_there_quantifiers_1": {
+      "acc,none": 0.984,
+      "acc_stderr,none": 0.00396985639031942,
+      "alias": " - blimp_existential_there_quantifiers_1"
+    },
+    "blimp_existential_there_quantifiers_2": {
+      "acc,none": 0.274,
+      "acc_stderr,none": 0.014111099288259585,
+      "alias": " - blimp_existential_there_quantifiers_2"
+    },
+    "blimp_existential_there_subject_raising": {
+      "acc,none": 0.91,
+      "acc_stderr,none": 0.009054390204866435,
+      "alias": " - blimp_existential_there_subject_raising"
+    },
+    "blimp_expletive_it_object_raising": {
+      "acc,none": 0.794,
+      "acc_stderr,none": 0.01279561361278654,
+      "alias": " - blimp_expletive_it_object_raising"
+    },
+    "blimp_inchoative": {
+      "acc,none": 0.617,
+      "acc_stderr,none": 0.015380102325652715,
+      "alias": " - blimp_inchoative"
+    },
+    "blimp_intransitive": {
+      "acc,none": 0.777,
+      "acc_stderr,none": 0.013169830843425679,
+      "alias": " - blimp_intransitive"
+    },
+    "blimp_irregular_past_participle_adjectives": {
+      "acc,none": 0.929,
+      "acc_stderr,none": 0.008125578442487914,
+      "alias": " - blimp_irregular_past_participle_adjectives"
+    },
+    "blimp_irregular_past_participle_verbs": {
+      "acc,none": 0.891,
+      "acc_stderr,none": 0.009859828407037188,
+      "alias": " - blimp_irregular_past_participle_verbs"
+    },
+    "blimp_irregular_plural_subject_verb_agreement_1": {
+      "acc,none": 0.926,
+      "acc_stderr,none": 0.008282064512704156,
+      "alias": " - blimp_irregular_plural_subject_verb_agreement_1"
+    },
+    "blimp_irregular_plural_subject_verb_agreement_2": {
+      "acc,none": 0.915,
+      "acc_stderr,none": 0.008823426366942314,
+      "alias": " - blimp_irregular_plural_subject_verb_agreement_2"
+    },
+    "blimp_left_branch_island_echo_question": {
+      "acc,none": 0.623,
+      "acc_stderr,none": 0.015333170125779843,
+      "alias": " - blimp_left_branch_island_echo_question"
+    },
+    "blimp_left_branch_island_simple_question": {
+      "acc,none": 0.917,
+      "acc_stderr,none": 0.008728527206074796,
+      "alias": " - blimp_left_branch_island_simple_question"
+    },
+    "blimp_matrix_question_npi_licensor_present": {
+      "acc,none": 0.438,
+      "acc_stderr,none": 0.01569721001969469,
+      "alias": " - blimp_matrix_question_npi_licensor_present"
+    },
+    "blimp_npi_present_1": {
+      "acc,none": 0.606,
+      "acc_stderr,none": 0.015459721957493375,
+      "alias": " - blimp_npi_present_1"
+    },
+    "blimp_npi_present_2": {
+      "acc,none": 0.568,
+      "acc_stderr,none": 0.015672320237336213,
+      "alias": " - blimp_npi_present_2"
+    },
+    "blimp_only_npi_licensor_present": {
+      "acc,none": 0.867,
+      "acc_stderr,none": 0.010743669132397344,
+      "alias": " - blimp_only_npi_licensor_present"
+    },
+    "blimp_only_npi_scope": {
+      "acc,none": 0.586,
+      "acc_stderr,none": 0.015583544104177527,
+      "alias": " - blimp_only_npi_scope"
+    },
+    "blimp_passive_1": {
+      "acc,none": 0.891,
+      "acc_stderr,none": 0.009859828407037188,
+      "alias": " - blimp_passive_1"
+    },
+    "blimp_passive_2": {
+      "acc,none": 0.896,
+      "acc_stderr,none": 0.009658016218524294,
+      "alias": " - blimp_passive_2"
+    },
+    "blimp_principle_A_c_command": {
+      "acc,none": 0.766,
+      "acc_stderr,none": 0.01339490288966001,
+      "alias": " - blimp_principle_A_c_command"
+    },
+    "blimp_principle_A_case_1": {
+      "acc,none": 1.0,
+      "acc_stderr,none": 0.0,
+      "alias": " - blimp_principle_A_case_1"
+    },
+    "blimp_principle_A_case_2": {
+      "acc,none": 0.942,
+      "acc_stderr,none": 0.007395315455792926,
+      "alias": " - blimp_principle_A_case_2"
+    },
+    "blimp_principle_A_domain_1": {
+      "acc,none": 0.997,
+      "acc_stderr,none": 0.001730316154346939,
+      "alias": " - blimp_principle_A_domain_1"
+    },
+    "blimp_principle_A_domain_2": {
+      "acc,none": 0.904,
+      "acc_stderr,none": 0.009320454434783243,
+      "alias": " - blimp_principle_A_domain_2"
+    },
+    "blimp_principle_A_domain_3": {
+      "acc,none": 0.831,
+      "acc_stderr,none": 0.01185662597789013,
+      "alias": " - blimp_principle_A_domain_3"
+    },
+    "blimp_principle_A_reconstruction": {
+      "acc,none": 0.485,
+      "acc_stderr,none": 0.015812179641814895,
+      "alias": " - blimp_principle_A_reconstruction"
+    },
+    "blimp_regular_plural_subject_verb_agreement_1": {
+      "acc,none": 0.948,
+      "acc_stderr,none": 0.007024624213817139,
+      "alias": " - blimp_regular_plural_subject_verb_agreement_1"
+    },
+    "blimp_regular_plural_subject_verb_agreement_2": {
+      "acc,none": 0.884,
+      "acc_stderr,none": 0.010131468138756967,
+      "alias": " - blimp_regular_plural_subject_verb_agreement_2"
+    },
+    "blimp_sentential_negation_npi_licensor_present": {
+      "acc,none": 0.991,
+      "acc_stderr,none": 0.0029879638431426513,
+      "alias": " - blimp_sentential_negation_npi_licensor_present"
+    },
+    "blimp_sentential_negation_npi_scope": {
+      "acc,none": 0.744,
+      "acc_stderr,none": 0.013807775152234206,
+      "alias": " - blimp_sentential_negation_npi_scope"
+    },
+    "blimp_sentential_subject_island": {
+      "acc,none": 0.452,
+      "acc_stderr,none": 0.015746235865880677,
+      "alias": " - blimp_sentential_subject_island"
+    },
+    "blimp_superlative_quantifiers_1": {
+      "acc,none": 0.911,
+      "acc_stderr,none": 0.009008893392651523,
+      "alias": " - blimp_superlative_quantifiers_1"
+    },
+    "blimp_superlative_quantifiers_2": {
+      "acc,none": 0.956,
+      "acc_stderr,none": 0.006488921798427425,
+      "alias": " - blimp_superlative_quantifiers_2"
+    },
+    "blimp_tough_vs_raising_1": {
+      "acc,none": 0.617,
+      "acc_stderr,none": 0.015380102325652699,
+      "alias": " - blimp_tough_vs_raising_1"
+    },
+    "blimp_tough_vs_raising_2": {
+      "acc,none": 0.875,
+      "acc_stderr,none": 0.010463483381956722,
+      "alias": " - blimp_tough_vs_raising_2"
+    },
+    "blimp_transitive": {
+      "acc,none": 0.88,
+      "acc_stderr,none": 0.01028132801274739,
+      "alias": " - blimp_transitive"
+    },
+    "blimp_wh_island": {
+      "acc,none": 0.817,
+      "acc_stderr,none": 0.012233587399477825,
+      "alias": " - blimp_wh_island"
+    },
+    "blimp_wh_questions_object_gap": {
+      "acc,none": 0.857,
+      "acc_stderr,none": 0.01107581480856704,
+      "alias": " - blimp_wh_questions_object_gap"
+    },
+    "blimp_wh_questions_subject_gap": {
+      "acc,none": 0.943,
+      "acc_stderr,none": 0.007335175853706826,
+      "alias": " - blimp_wh_questions_subject_gap"
+    },
+    "blimp_wh_questions_subject_gap_long_distance": {
+      "acc,none": 0.934,
+      "acc_stderr,none": 0.0078552979386976,
+      "alias": " - blimp_wh_questions_subject_gap_long_distance"
+    },
+    "blimp_wh_vs_that_no_gap": {
+      "acc,none": 0.984,
+      "acc_stderr,none": 0.003969856390319412,
+      "alias": " - blimp_wh_vs_that_no_gap"
+    },
+    "blimp_wh_vs_that_no_gap_long_distance": {
+      "acc,none": 0.973,
+      "acc_stderr,none": 0.00512808904927529,
+      "alias": " - blimp_wh_vs_that_no_gap_long_distance"
+    },
+    "blimp_wh_vs_that_with_gap": {
+      "acc,none": 0.41,
+      "acc_stderr,none": 0.015560917136921662,
+      "alias": " - blimp_wh_vs_that_with_gap"
+    },
+    "blimp_wh_vs_that_with_gap_long_distance": {
+      "acc,none": 0.353,
+      "acc_stderr,none": 0.015120172605483694,
+      "alias": " - blimp_wh_vs_that_with_gap_long_distance"
+    }
+  },
+  "groups": {
+    "blimp": {
+      "acc,none": 0.8223731343283582,
+      "acc_stderr,none": 0.16119006470239358,
+      "alias": "blimp"
+    }
+  },
+  "configs": {
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    },
+    "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": 1.0
+      }
+    }
+  },
+  "versions": {
+    "blimp": "N/A",
+    "blimp_adjunct_island": 1.0,
+    "blimp_anaphor_gender_agreement": 1.0,
+    "blimp_anaphor_number_agreement": 1.0,
+    "blimp_animate_subject_passive": 1.0,
+    "blimp_animate_subject_trans": 1.0,
+    "blimp_causative": 1.0,
+    "blimp_complex_NP_island": 1.0,
+    "blimp_coordinate_structure_constraint_complex_left_branch": 1.0,
+    "blimp_coordinate_structure_constraint_object_extraction": 1.0,
+    "blimp_determiner_noun_agreement_1": 1.0,
+    "blimp_determiner_noun_agreement_2": 1.0,
+    "blimp_determiner_noun_agreement_irregular_1": 1.0,
+    "blimp_determiner_noun_agreement_irregular_2": 1.0,
+    "blimp_determiner_noun_agreement_with_adj_2": 1.0,
+    "blimp_determiner_noun_agreement_with_adj_irregular_1": 1.0,
+    "blimp_determiner_noun_agreement_with_adj_irregular_2": 1.0,
+    "blimp_determiner_noun_agreement_with_adjective_1": 1.0,
+    "blimp_distractor_agreement_relational_noun": 1.0,
+    "blimp_distractor_agreement_relative_clause": 1.0,
+    "blimp_drop_argument": 1.0,
+    "blimp_ellipsis_n_bar_1": 1.0,
+    "blimp_ellipsis_n_bar_2": 1.0,
+    "blimp_existential_there_object_raising": 1.0,
+    "blimp_existential_there_quantifiers_1": 1.0,
+    "blimp_existential_there_quantifiers_2": 1.0,
+    "blimp_existential_there_subject_raising": 1.0,
+    "blimp_expletive_it_object_raising": 1.0,
+    "blimp_inchoative": 1.0,
+    "blimp_intransitive": 1.0,
+    "blimp_irregular_past_participle_adjectives": 1.0,
+    "blimp_irregular_past_participle_verbs": 1.0,
+    "blimp_irregular_plural_subject_verb_agreement_1": 1.0,
+    "blimp_irregular_plural_subject_verb_agreement_2": 1.0,
+    "blimp_left_branch_island_echo_question": 1.0,
+    "blimp_left_branch_island_simple_question": 1.0,
+    "blimp_matrix_question_npi_licensor_present": 1.0,
+    "blimp_npi_present_1": 1.0,
+    "blimp_npi_present_2": 1.0,
+    "blimp_only_npi_licensor_present": 1.0,
+    "blimp_only_npi_scope": 1.0,
+    "blimp_passive_1": 1.0,
+    "blimp_passive_2": 1.0,
+    "blimp_principle_A_c_command": 1.0,
+    "blimp_principle_A_case_1": 1.0,
+    "blimp_principle_A_case_2": 1.0,
+    "blimp_principle_A_domain_1": 1.0,
+    "blimp_principle_A_domain_2": 1.0,
+    "blimp_principle_A_domain_3": 1.0,
+    "blimp_principle_A_reconstruction": 1.0,
+    "blimp_regular_plural_subject_verb_agreement_1": 1.0,
+    "blimp_regular_plural_subject_verb_agreement_2": 1.0,
+    "blimp_sentential_negation_npi_licensor_present": 1.0,
+    "blimp_sentential_negation_npi_scope": 1.0,
+    "blimp_sentential_subject_island": 1.0,
+    "blimp_superlative_quantifiers_1": 1.0,
+    "blimp_superlative_quantifiers_2": 1.0,
+    "blimp_tough_vs_raising_1": 1.0,
+    "blimp_tough_vs_raising_2": 1.0,
+    "blimp_transitive": 1.0,
+    "blimp_wh_island": 1.0,
+    "blimp_wh_questions_object_gap": 1.0,
+    "blimp_wh_questions_subject_gap": 1.0,
+    "blimp_wh_questions_subject_gap_long_distance": 1.0,
+    "blimp_wh_vs_that_no_gap": 1.0,
+    "blimp_wh_vs_that_no_gap_long_distance": 1.0,
+    "blimp_wh_vs_that_with_gap": 1.0,
+    "blimp_wh_vs_that_with_gap_long_distance": 1.0
+  },
+  "n-shot": {
+    "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
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/R4-7B-15t-No-Mask_pth,dtype=bfloat16,trust_remote_code=True",
+    "batch_size": "auto",
+    "batch_sizes": [
+      64
+    ],
+    "device": null,
+    "use_cache": null,
+    "limit": null,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": null
+  },
+  "git_hash": "8281e96"
+}

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/blimp/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:124f31d4c9170308c2fae50d85a1d593c8fb9353a0b082d246ec739c0724a4ba
+size 324266

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/cmmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e3b899a3bcdd9a3798013caa514c6802576ce96938ba0007edab9e3632047091
+size 116540

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,67 @@
+{
+  "results": {
+    "hellaswag": {
+      "acc,none": 0.5258912567217686,
+      "acc_stderr,none": 0.004983087049281747,
+      "acc_norm,none": 0.7099183429595698,
+      "acc_norm_stderr,none": 0.00452872395187824,
+      "alias": "hellaswag"
+    }
+  },
+  "configs": {
+    "hellaswag": {
+      "task": "hellaswag",
+      "group": [
+        "multiple_choice"
+      ],
+      "dataset_path": "hellaswag",
+      "training_split": "train",
+      "validation_split": "validation",
+      "process_docs": "def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:\n    def _process_doc(doc):\n        ctx = doc[\"ctx_a\"] + \" \" + doc[\"ctx_b\"].capitalize()\n        out_doc = {\n            \"query\": preprocess(doc[\"activity_label\"] + \": \" + ctx),\n            \"choices\": [preprocess(ending) for ending in doc[\"endings\"]],\n            \"gold\": int(doc[\"label\"]),\n        }\n        return out_doc\n\n    return dataset.map(_process_doc)\n",
+      "doc_to_text": "{{query}}",
+      "doc_to_target": "{{label}}",
+      "doc_to_choice": "choices",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "acc_norm",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    }
+  },
+  "versions": {
+    "hellaswag": 1.0
+  },
+  "n-shot": {
+    "hellaswag": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/R4-7B-15t-No-Mask_pth,dtype=bfloat16,trust_remote_code=True",
+    "batch_size": "auto",
+    "batch_sizes": [
+      64
+    ],
+    "device": null,
+    "use_cache": null,
+    "limit": null,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": null
+  },
+  "git_hash": "8281e96"
+}

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1c50c3af8140d29ff67a5f74f04a141a7603e730136ef24c83a6dfad9e8e4a6b
+size 50753

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/lambada/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,126 @@
+{
+  "results": {
+    "lambada": {
+      "perplexity,none": 3.8784881294998965,
+      "perplexity_stderr,none": 0.23551879245757332,
+      "acc,none": 0.7087133708519309,
+      "acc_stderr,none": 0.016850692633428886,
+      "alias": "lambada"
+    },
+    "lambada_openai": {
+      "perplexity,none": 3.435839806000842,
+      "perplexity_stderr,none": 0.06696344523500707,
+      "acc,none": 0.7399573064234427,
+      "acc_stderr,none": 0.00611135809828806,
+      "alias": " - lambada_openai"
+    },
+    "lambada_standard": {
+      "perplexity,none": 4.321136452998951,
+      "perplexity_stderr,none": 0.09207106981169363,
+      "acc,none": 0.6774694352804191,
+      "acc_stderr,none": 0.0065124194470117,
+      "alias": " - lambada_standard"
+    }
+  },
+  "groups": {
+    "lambada": {
+      "perplexity,none": 3.8784881294998965,
+      "perplexity_stderr,none": 0.23551879245757332,
+      "acc,none": 0.7087133708519309,
+      "acc_stderr,none": 0.016850692633428886,
+      "alias": "lambada"
+    }
+  },
+  "configs": {
+    "lambada_openai": {
+      "task": "lambada_openai",
+      "group": [
+        "lambada"
+      ],
+      "dataset_path": "EleutherAI/lambada_openai",
+      "dataset_name": "default",
+      "test_split": "test",
+      "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
+      "doc_to_target": "{{' '+text.split(' ')[-1]}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "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": 1.0
+      }
+    },
+    "lambada_standard": {
+      "task": "lambada_standard",
+      "group": [
+        "lambada"
+      ],
+      "dataset_path": "lambada",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
+      "doc_to_target": "{{' '+text.split(' ')[-1]}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "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": 1.0
+      }
+    }
+  },
+  "versions": {
+    "lambada": "N/A",
+    "lambada_openai": 1.0,
+    "lambada_standard": 1.0
+  },
+  "n-shot": {
+    "lambada": 0,
+    "lambada_openai": 0,
+    "lambada_standard": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/R4-7B-15t-No-Mask_pth,dtype=bfloat16,trust_remote_code=True",
+    "batch_size": "auto",
+    "batch_sizes": [
+      64
+    ],
+    "device": null,
+    "use_cache": null,
+    "limit": null,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": null
+  },
+  "git_hash": "8281e96"
+}

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/lambada/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b5469c918dc9db04f1bc7ca239527c4dbd8b3cac25b1e9886ec6e9374b9765a1
+size 47978

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,252 @@
+{
+  "results": {
+    "lambada_multilingual": {
+      "perplexity,none": 20.70048891120678,
+      "perplexity_stderr,none": 8.059465734784938,
+      "acc,none": 0.5369687560644285,
+      "acc_stderr,none": 0.08430882353217248,
+      "alias": "lambada_multilingual"
+    },
+    "lambada_openai_mt_de": {
+      "perplexity,none": 34.04622392997292,
+      "perplexity_stderr,none": 1.8391447472790967,
+      "acc,none": 0.42286046962934215,
+      "acc_stderr,none": 0.0068825761876977875,
+      "alias": " - lambada_openai_mt_de"
+    },
+    "lambada_openai_mt_en": {
+      "perplexity,none": 3.4357348930487683,
+      "perplexity_stderr,none": 0.06697837838975183,
+      "acc,none": 0.7403454298466913,
+      "acc_stderr,none": 0.006108397042730499,
+      "alias": " - lambada_openai_mt_en"
+    },
+    "lambada_openai_mt_es": {
+      "perplexity,none": 28.25835836046741,
+      "perplexity_stderr,none": 1.3682644328702065,
+      "acc,none": 0.45526877547059963,
+      "acc_stderr,none": 0.006938045450999903,
+      "alias": " - lambada_openai_mt_es"
+    },
+    "lambada_openai_mt_fr": {
+      "perplexity,none": 16.19056770863486,
+      "perplexity_stderr,none": 0.7674221220205246,
+      "acc,none": 0.5513293227246264,
+      "acc_stderr,none": 0.006929173919665485,
+      "alias": " - lambada_openai_mt_fr"
+    },
+    "lambada_openai_mt_it": {
+      "perplexity,none": 21.571559663909937,
+      "perplexity_stderr,none": 1.1208902713252802,
+      "acc,none": 0.515039782650883,
+      "acc_stderr,none": 0.006962825604553246,
+      "alias": " - lambada_openai_mt_it"
+    }
+  },
+  "groups": {
+    "lambada_multilingual": {
+      "perplexity,none": 20.70048891120678,
+      "perplexity_stderr,none": 8.059465734784938,
+      "acc,none": 0.5369687560644285,
+      "acc_stderr,none": 0.08430882353217248,
+      "alias": "lambada_multilingual"
+    }
+  },
+  "configs": {
+    "lambada_openai_mt_de": {
+      "task": "lambada_openai_mt_de",
+      "group": [
+        "lambada_multilingual"
+      ],
+      "dataset_path": "EleutherAI/lambada_openai",
+      "dataset_name": "de",
+      "test_split": "test",
+      "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
+      "doc_to_target": "{{' '+text.split(' ')[-1]}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "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": 1.0
+      }
+    },
+    "lambada_openai_mt_en": {
+      "task": "lambada_openai_mt_en",
+      "group": [
+        "lambada_multilingual"
+      ],
+      "dataset_path": "EleutherAI/lambada_openai",
+      "dataset_name": "en",
+      "test_split": "test",
+      "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
+      "doc_to_target": "{{' '+text.split(' ')[-1]}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "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": 1.0
+      }
+    },
+    "lambada_openai_mt_es": {
+      "task": "lambada_openai_mt_es",
+      "group": [
+        "lambada_multilingual"
+      ],
+      "dataset_path": "EleutherAI/lambada_openai",
+      "dataset_name": "es",
+      "test_split": "test",
+      "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
+      "doc_to_target": "{{' '+text.split(' ')[-1]}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "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": 1.0
+      }
+    },
+    "lambada_openai_mt_fr": {
+      "task": "lambada_openai_mt_fr",
+      "group": [
+        "lambada_multilingual"
+      ],
+      "dataset_path": "EleutherAI/lambada_openai",
+      "dataset_name": "fr",
+      "test_split": "test",
+      "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
+      "doc_to_target": "{{' '+text.split(' ')[-1]}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "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": 1.0
+      }
+    },
+    "lambada_openai_mt_it": {
+      "task": "lambada_openai_mt_it",
+      "group": [
+        "lambada_multilingual"
+      ],
+      "dataset_path": "EleutherAI/lambada_openai",
+      "dataset_name": "it",
+      "test_split": "test",
+      "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
+      "doc_to_target": "{{' '+text.split(' ')[-1]}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "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": 1.0
+      }
+    }
+  },
+  "versions": {
+    "lambada_multilingual": "N/A",
+    "lambada_openai_mt_de": 1.0,
+    "lambada_openai_mt_en": 1.0,
+    "lambada_openai_mt_es": 1.0,
+    "lambada_openai_mt_fr": 1.0,
+    "lambada_openai_mt_it": 1.0
+  },
+  "n-shot": {
+    "lambada_multilingual": 0,
+    "lambada_openai_mt_de": 0,
+    "lambada_openai_mt_en": 0,
+    "lambada_openai_mt_es": 0,
+    "lambada_openai_mt_fr": 0,
+    "lambada_openai_mt_it": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/R4-7B-15t-No-Mask_pth,dtype=bfloat16,trust_remote_code=True",
+    "batch_size": "auto",
+    "batch_sizes": [
+      64
+    ],
+    "device": null,
+    "use_cache": null,
+    "limit": null,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": null
+  },
+  "git_hash": "8281e96"
+}

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f912cb82f9caef9babb3bce391dc6f94d190bd2e02b50e0fdf4fb56fcf840bca
+size 65618

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/logiqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,66 @@
+{
+  "results": {
+    "logiqa": {
+      "acc,none": 0.23195084485407066,
+      "acc_stderr,none": 0.016555252497925898,
+      "acc_norm,none": 0.2887864823348694,
+      "acc_norm_stderr,none": 0.017775906336539235,
+      "alias": "logiqa"
+    }
+  },
+  "configs": {
+    "logiqa": {
+      "task": "logiqa",
+      "dataset_path": "EleutherAI/logiqa",
+      "dataset_name": "logiqa",
+      "training_split": "train",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text(doc) -> str:\n    \"\"\"\n    Passage: <passage>\n    Question: <question>\n    Choices:\n    A. <choice1>\n    B. <choice2>\n    C. <choice3>\n    D. <choice4>\n    Answer:\n    \"\"\"\n    choices = [\"a\", \"b\", \"c\", \"d\"]\n    prompt = \"Passage: \" + doc[\"context\"] + \"\\n\"\n    prompt += \"Question: \" + doc[\"question\"] + \"\\nChoices:\\n\"\n    for choice, option in zip(choices, doc[\"options\"]):\n        prompt += f\"{choice.upper()}. {option}\\n\"\n    prompt += \"Answer:\"\n    return prompt\n",
+      "doc_to_target": "def doc_to_target(doc) -> int:\n    choices = [\"a\", \"b\", \"c\", \"d\"]\n    return choices.index(doc[\"label\"].strip())\n",
+      "doc_to_choice": "{{options}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "acc_norm",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": true,
+      "doc_to_decontamination_query": "{{context}}",
+      "metadata": {
+        "version": 1.0
+      }
+    }
+  },
+  "versions": {
+    "logiqa": 1.0
+  },
+  "n-shot": {
+    "logiqa": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/R4-7B-15t-No-Mask_pth,dtype=bfloat16,trust_remote_code=True",
+    "batch_size": "auto",
+    "batch_sizes": [
+      32
+    ],
+    "device": null,
+    "use_cache": null,
+    "limit": null,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": null
+  },
+  "git_hash": "8281e96"
+}

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/logiqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:67299b15bf7137fdc150e91007bcbf9159bcaa7ba0b9ae070f8d308cca86df29
+size 46560

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,2594 @@
+{
+  "results": {
+    "mmlu": {
+      "acc,none": 0.2829369035749893,
+      "acc_stderr,none": 0.04449010491367579,
+      "alias": "mmlu"
+    },
+    "mmlu_humanities": {
+      "alias": " - humanities",
+      "acc,none": 0.27290116896918176,
+      "acc_stderr,none": 0.034599615055619884
+    },
+    "mmlu_formal_logic": {
+      "alias": "  - formal_logic",
+      "acc,none": 0.31746031746031744,
+      "acc_stderr,none": 0.04163453031302859
+    },
+    "mmlu_high_school_european_history": {
+      "alias": "  - high_school_european_history",
+      "acc,none": 0.3212121212121212,
+      "acc_stderr,none": 0.03646204963253812
+    },
+    "mmlu_high_school_us_history": {
+      "alias": "  - high_school_us_history",
+      "acc,none": 0.29411764705882354,
+      "acc_stderr,none": 0.03198001660115071
+    },
+    "mmlu_high_school_world_history": {
+      "alias": "  - high_school_world_history",
+      "acc,none": 0.28270042194092826,
+      "acc_stderr,none": 0.029312814153955934
+    },
+    "mmlu_international_law": {
+      "alias": "  - international_law",
+      "acc,none": 0.3140495867768595,
+      "acc_stderr,none": 0.042369647530410184
+    },
+    "mmlu_jurisprudence": {
+      "alias": "  - jurisprudence",
+      "acc,none": 0.3148148148148148,
+      "acc_stderr,none": 0.04489931073591312
+    },
+    "mmlu_logical_fallacies": {
+      "alias": "  - logical_fallacies",
+      "acc,none": 0.26993865030674846,
+      "acc_stderr,none": 0.034878251684978906
+    },
+    "mmlu_moral_disputes": {
+      "alias": "  - moral_disputes",
+      "acc,none": 0.27167630057803466,
+      "acc_stderr,none": 0.023948512905468365
+    },
+    "mmlu_moral_scenarios": {
+      "alias": "  - moral_scenarios",
+      "acc,none": 0.23910614525139665,
+      "acc_stderr,none": 0.014265554192331154
+    },
+    "mmlu_philosophy": {
+      "alias": "  - philosophy",
+      "acc,none": 0.33762057877813506,
+      "acc_stderr,none": 0.02685882587948854
+    },
+    "mmlu_prehistory": {
+      "alias": "  - prehistory",
+      "acc,none": 0.2839506172839506,
+      "acc_stderr,none": 0.025089478523765134
+    },
+    "mmlu_professional_law": {
+      "alias": "  - professional_law",
+      "acc,none": 0.2516297262059974,
+      "acc_stderr,none": 0.011083276280441909
+    },
+    "mmlu_world_religions": {
+      "alias": "  - world_religions",
+      "acc,none": 0.3333333333333333,
+      "acc_stderr,none": 0.036155076303109365
+    },
+    "mmlu_other": {
+      "alias": " - other",
+      "acc,none": 0.31412938525909234,
+      "acc_stderr,none": 0.04595175653871959
+    },
+    "mmlu_business_ethics": {
+      "alias": "  - business_ethics",
+      "acc,none": 0.29,
+      "acc_stderr,none": 0.045604802157206845
+    },
+    "mmlu_clinical_knowledge": {
+      "alias": "  - clinical_knowledge",
+      "acc,none": 0.3320754716981132,
+      "acc_stderr,none": 0.028985455652334388
+    },
+    "mmlu_college_medicine": {
+      "alias": "  - college_medicine",
+      "acc,none": 0.21965317919075145,
+      "acc_stderr,none": 0.031568093627031744
+    },
+    "mmlu_global_facts": {
+      "alias": "  - global_facts",
+      "acc,none": 0.33,
+      "acc_stderr,none": 0.04725815626252605
+    },
+    "mmlu_human_aging": {
+      "alias": "  - human_aging",
+      "acc,none": 0.3811659192825112,
+      "acc_stderr,none": 0.03259625118416828
+    },
+    "mmlu_management": {
+      "alias": "  - management",
+      "acc,none": 0.2912621359223301,
+      "acc_stderr,none": 0.044986763205729224
+    },
+    "mmlu_marketing": {
+      "alias": "  - marketing",
+      "acc,none": 0.3247863247863248,
+      "acc_stderr,none": 0.03067902276549883
+    },
+    "mmlu_medical_genetics": {
+      "alias": "  - medical_genetics",
+      "acc,none": 0.28,
+      "acc_stderr,none": 0.04512608598542127
+    },
+    "mmlu_miscellaneous": {
+      "alias": "  - miscellaneous",
+      "acc,none": 0.3652618135376756,
+      "acc_stderr,none": 0.01721853002883865
+    },
+    "mmlu_nutrition": {
+      "alias": "  - nutrition",
+      "acc,none": 0.29411764705882354,
+      "acc_stderr,none": 0.026090162504279046
+    },
+    "mmlu_professional_accounting": {
+      "alias": "  - professional_accounting",
+      "acc,none": 0.25886524822695034,
+      "acc_stderr,none": 0.026129572527180848
+    },
+    "mmlu_professional_medicine": {
+      "alias": "  - professional_medicine",
+      "acc,none": 0.2426470588235294,
+      "acc_stderr,none": 0.02604066247420126
+    },
+    "mmlu_virology": {
+      "alias": "  - virology",
+      "acc,none": 0.3253012048192771,
+      "acc_stderr,none": 0.03647168523683227
+    },
+    "mmlu_social_sciences": {
+      "alias": " - social_sciences",
+      "acc,none": 0.27331816704582385,
+      "acc_stderr,none": 0.04044627009055694
+    },
+    "mmlu_econometrics": {
+      "alias": "  - econometrics",
+      "acc,none": 0.23684210526315788,
+      "acc_stderr,none": 0.03999423879281338
+    },
+    "mmlu_high_school_geography": {
+      "alias": "  - high_school_geography",
+      "acc,none": 0.29292929292929293,
+      "acc_stderr,none": 0.032424979581788166
+    },
+    "mmlu_high_school_government_and_politics": {
+      "alias": "  - high_school_government_and_politics",
+      "acc,none": 0.34196891191709844,
+      "acc_stderr,none": 0.03423465100104282
+    },
+    "mmlu_high_school_macroeconomics": {
+      "alias": "  - high_school_macroeconomics",
+      "acc,none": 0.23846153846153847,
+      "acc_stderr,none": 0.02160629449464773
+    },
+    "mmlu_high_school_microeconomics": {
+      "alias": "  - high_school_microeconomics",
+      "acc,none": 0.2689075630252101,
+      "acc_stderr,none": 0.028801392193631273
+    },
+    "mmlu_high_school_psychology": {
+      "alias": "  - high_school_psychology",
+      "acc,none": 0.27706422018348625,
+      "acc_stderr,none": 0.019188482590169538
+    },
+    "mmlu_human_sexuality": {
+      "alias": "  - human_sexuality",
+      "acc,none": 0.29770992366412213,
+      "acc_stderr,none": 0.040103589424622034
+    },
+    "mmlu_professional_psychology": {
+      "alias": "  - professional_psychology",
+      "acc,none": 0.27941176470588236,
+      "acc_stderr,none": 0.018152871051538802
+    },
+    "mmlu_public_relations": {
+      "alias": "  - public_relations",
+      "acc,none": 0.36363636363636365,
+      "acc_stderr,none": 0.04607582090719976
+    },
+    "mmlu_security_studies": {
+      "alias": "  - security_studies",
+      "acc,none": 0.2,
+      "acc_stderr,none": 0.025607375986579164
+    },
+    "mmlu_sociology": {
+      "alias": "  - sociology",
+      "acc,none": 0.2935323383084577,
+      "acc_stderr,none": 0.03220024104534205
+    },
+    "mmlu_us_foreign_policy": {
+      "alias": "  - us_foreign_policy",
+      "acc,none": 0.24,
+      "acc_stderr,none": 0.04292346959909284
+    },
+    "mmlu_stem": {
+      "alias": " - stem",
+      "acc,none": 0.2765620044402157,
+      "acc_stderr,none": 0.052108661789192635
+    },
+    "mmlu_abstract_algebra": {
+      "alias": "  - abstract_algebra",
+      "acc,none": 0.25,
+      "acc_stderr,none": 0.04351941398892446
+    },
+    "mmlu_anatomy": {
+      "alias": "  - anatomy",
+      "acc,none": 0.34074074074074073,
+      "acc_stderr,none": 0.040943762699967926
+    },
+    "mmlu_astronomy": {
+      "alias": "  - astronomy",
+      "acc,none": 0.29605263157894735,
+      "acc_stderr,none": 0.03715062154998905
+    },
+    "mmlu_college_biology": {
+      "alias": "  - college_biology",
+      "acc,none": 0.2916666666666667,
+      "acc_stderr,none": 0.038009680605548594
+    },
+    "mmlu_college_chemistry": {
+      "alias": "  - college_chemistry",
+      "acc,none": 0.24,
+      "acc_stderr,none": 0.04292346959909282
+    },
+    "mmlu_college_computer_science": {
+      "alias": "  - college_computer_science",
+      "acc,none": 0.2,
+      "acc_stderr,none": 0.04020151261036846
+    },
+    "mmlu_college_mathematics": {
+      "alias": "  - college_mathematics",
+      "acc,none": 0.22,
+      "acc_stderr,none": 0.0416333199893227
+    },
+    "mmlu_college_physics": {
+      "alias": "  - college_physics",
+      "acc,none": 0.18627450980392157,
+      "acc_stderr,none": 0.03873958714149352
+    },
+    "mmlu_computer_security": {
+      "alias": "  - computer_security",
+      "acc,none": 0.3,
+      "acc_stderr,none": 0.046056618647183814
+    },
+    "mmlu_conceptual_physics": {
+      "alias": "  - conceptual_physics",
+      "acc,none": 0.33191489361702126,
+      "acc_stderr,none": 0.030783736757745643
+    },
+    "mmlu_electrical_engineering": {
+      "alias": "  - electrical_engineering",
+      "acc,none": 0.2689655172413793,
+      "acc_stderr,none": 0.03695183311650232
+    },
+    "mmlu_elementary_mathematics": {
+      "alias": "  - elementary_mathematics",
+      "acc,none": 0.25925925925925924,
+      "acc_stderr,none": 0.022569897074918428
+    },
+    "mmlu_high_school_biology": {
+      "alias": "  - high_school_biology",
+      "acc,none": 0.34838709677419355,
+      "acc_stderr,none": 0.02710482632810094
+    },
+    "mmlu_high_school_chemistry": {
+      "alias": "  - high_school_chemistry",
+      "acc,none": 0.2561576354679803,
+      "acc_stderr,none": 0.030712730070982592
+    },
+    "mmlu_high_school_computer_science": {
+      "alias": "  - high_school_computer_science",
+      "acc,none": 0.33,
+      "acc_stderr,none": 0.047258156262526045
+    },
+    "mmlu_high_school_mathematics": {
+      "alias": "  - high_school_mathematics",
+      "acc,none": 0.27037037037037037,
+      "acc_stderr,none": 0.02708037281514566
+    },
+    "mmlu_high_school_physics": {
+      "alias": "  - high_school_physics",
+      "acc,none": 0.271523178807947,
+      "acc_stderr,none": 0.03631329803969653
+    },
+    "mmlu_high_school_statistics": {
+      "alias": "  - high_school_statistics",
+      "acc,none": 0.18518518518518517,
+      "acc_stderr,none": 0.026491914727355168
+    },
+    "mmlu_machine_learning": {
+      "alias": "  - machine_learning",
+      "acc,none": 0.33035714285714285,
+      "acc_stderr,none": 0.04464285714285713
+    }
+  },
+  "groups": {
+    "mmlu": {
+      "acc,none": 0.2829369035749893,
+      "acc_stderr,none": 0.04449010491367579,
+      "alias": "mmlu"
+    },
+    "mmlu_humanities": {
+      "alias": " - humanities",
+      "acc,none": 0.27290116896918176,
+      "acc_stderr,none": 0.034599615055619884
+    },
+    "mmlu_other": {
+      "alias": " - other",
+      "acc,none": 0.31412938525909234,
+      "acc_stderr,none": 0.04595175653871959
+    },
+    "mmlu_social_sciences": {
+      "alias": " - social_sciences",
+      "acc,none": 0.27331816704582385,
+      "acc_stderr,none": 0.04044627009055694
+    },
+    "mmlu_stem": {
+      "alias": " - stem",
+      "acc,none": 0.2765620044402157,
+      "acc_stderr,none": 0.052108661789192635
+    }
+  },
+  "configs": {
+    "mmlu_abstract_algebra": {
+      "task": "mmlu_abstract_algebra",
+      "task_alias": "abstract_algebra",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "abstract_algebra",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_anatomy": {
+      "task": "mmlu_anatomy",
+      "task_alias": "anatomy",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "anatomy",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about anatomy.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_astronomy": {
+      "task": "mmlu_astronomy",
+      "task_alias": "astronomy",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "astronomy",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about astronomy.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_business_ethics": {
+      "task": "mmlu_business_ethics",
+      "task_alias": "business_ethics",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "business_ethics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about business ethics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_clinical_knowledge": {
+      "task": "mmlu_clinical_knowledge",
+      "task_alias": "clinical_knowledge",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "clinical_knowledge",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_college_biology": {
+      "task": "mmlu_college_biology",
+      "task_alias": "college_biology",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "college_biology",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about college biology.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_college_chemistry": {
+      "task": "mmlu_college_chemistry",
+      "task_alias": "college_chemistry",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "college_chemistry",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_college_computer_science": {
+      "task": "mmlu_college_computer_science",
+      "task_alias": "college_computer_science",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "college_computer_science",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about college computer science.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_college_mathematics": {
+      "task": "mmlu_college_mathematics",
+      "task_alias": "college_mathematics",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "college_mathematics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_college_medicine": {
+      "task": "mmlu_college_medicine",
+      "task_alias": "college_medicine",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "college_medicine",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about college medicine.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_college_physics": {
+      "task": "mmlu_college_physics",
+      "task_alias": "college_physics",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "college_physics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about college physics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_computer_security": {
+      "task": "mmlu_computer_security",
+      "task_alias": "computer_security",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "computer_security",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about computer security.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_conceptual_physics": {
+      "task": "mmlu_conceptual_physics",
+      "task_alias": "conceptual_physics",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "conceptual_physics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_econometrics": {
+      "task": "mmlu_econometrics",
+      "task_alias": "econometrics",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "econometrics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about econometrics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_electrical_engineering": {
+      "task": "mmlu_electrical_engineering",
+      "task_alias": "electrical_engineering",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "electrical_engineering",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_elementary_mathematics": {
+      "task": "mmlu_elementary_mathematics",
+      "task_alias": "elementary_mathematics",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "elementary_mathematics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_formal_logic": {
+      "task": "mmlu_formal_logic",
+      "task_alias": "formal_logic",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "formal_logic",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about formal logic.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_global_facts": {
+      "task": "mmlu_global_facts",
+      "task_alias": "global_facts",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "global_facts",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about global facts.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_biology": {
+      "task": "mmlu_high_school_biology",
+      "task_alias": "high_school_biology",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_biology",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school biology.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_chemistry": {
+      "task": "mmlu_high_school_chemistry",
+      "task_alias": "high_school_chemistry",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_chemistry",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_computer_science": {
+      "task": "mmlu_high_school_computer_science",
+      "task_alias": "high_school_computer_science",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_computer_science",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_european_history": {
+      "task": "mmlu_high_school_european_history",
+      "task_alias": "high_school_european_history",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_european_history",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school european history.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_geography": {
+      "task": "mmlu_high_school_geography",
+      "task_alias": "high_school_geography",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_geography",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school geography.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_government_and_politics": {
+      "task": "mmlu_high_school_government_and_politics",
+      "task_alias": "high_school_government_and_politics",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_government_and_politics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_macroeconomics": {
+      "task": "mmlu_high_school_macroeconomics",
+      "task_alias": "high_school_macroeconomics",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_macroeconomics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_mathematics": {
+      "task": "mmlu_high_school_mathematics",
+      "task_alias": "high_school_mathematics",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_mathematics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_microeconomics": {
+      "task": "mmlu_high_school_microeconomics",
+      "task_alias": "high_school_microeconomics",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_microeconomics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_physics": {
+      "task": "mmlu_high_school_physics",
+      "task_alias": "high_school_physics",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_physics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school physics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_psychology": {
+      "task": "mmlu_high_school_psychology",
+      "task_alias": "high_school_psychology",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_psychology",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_statistics": {
+      "task": "mmlu_high_school_statistics",
+      "task_alias": "high_school_statistics",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_statistics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_us_history": {
+      "task": "mmlu_high_school_us_history",
+      "task_alias": "high_school_us_history",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_us_history",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school us history.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_world_history": {
+      "task": "mmlu_high_school_world_history",
+      "task_alias": "high_school_world_history",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_world_history",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school world history.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_human_aging": {
+      "task": "mmlu_human_aging",
+      "task_alias": "human_aging",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "human_aging",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about human aging.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_human_sexuality": {
+      "task": "mmlu_human_sexuality",
+      "task_alias": "human_sexuality",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "human_sexuality",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_international_law": {
+      "task": "mmlu_international_law",
+      "task_alias": "international_law",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "international_law",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about international law.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_jurisprudence": {
+      "task": "mmlu_jurisprudence",
+      "task_alias": "jurisprudence",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "jurisprudence",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_logical_fallacies": {
+      "task": "mmlu_logical_fallacies",
+      "task_alias": "logical_fallacies",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "logical_fallacies",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_machine_learning": {
+      "task": "mmlu_machine_learning",
+      "task_alias": "machine_learning",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "machine_learning",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about machine learning.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_management": {
+      "task": "mmlu_management",
+      "task_alias": "management",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "management",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about management.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_marketing": {
+      "task": "mmlu_marketing",
+      "task_alias": "marketing",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "marketing",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about marketing.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_medical_genetics": {
+      "task": "mmlu_medical_genetics",
+      "task_alias": "medical_genetics",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "medical_genetics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_miscellaneous": {
+      "task": "mmlu_miscellaneous",
+      "task_alias": "miscellaneous",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "miscellaneous",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_moral_disputes": {
+      "task": "mmlu_moral_disputes",
+      "task_alias": "moral_disputes",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "moral_disputes",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_moral_scenarios": {
+      "task": "mmlu_moral_scenarios",
+      "task_alias": "moral_scenarios",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "moral_scenarios",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_nutrition": {
+      "task": "mmlu_nutrition",
+      "task_alias": "nutrition",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "nutrition",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about nutrition.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_philosophy": {
+      "task": "mmlu_philosophy",
+      "task_alias": "philosophy",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "philosophy",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about philosophy.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_prehistory": {
+      "task": "mmlu_prehistory",
+      "task_alias": "prehistory",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "prehistory",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about prehistory.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_professional_accounting": {
+      "task": "mmlu_professional_accounting",
+      "task_alias": "professional_accounting",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "professional_accounting",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_professional_law": {
+      "task": "mmlu_professional_law",
+      "task_alias": "professional_law",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "professional_law",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about professional law.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_professional_medicine": {
+      "task": "mmlu_professional_medicine",
+      "task_alias": "professional_medicine",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "professional_medicine",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_professional_psychology": {
+      "task": "mmlu_professional_psychology",
+      "task_alias": "professional_psychology",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "professional_psychology",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_public_relations": {
+      "task": "mmlu_public_relations",
+      "task_alias": "public_relations",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "public_relations",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about public relations.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_security_studies": {
+      "task": "mmlu_security_studies",
+      "task_alias": "security_studies",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "security_studies",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about security studies.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_sociology": {
+      "task": "mmlu_sociology",
+      "task_alias": "sociology",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "sociology",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about sociology.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_us_foreign_policy": {
+      "task": "mmlu_us_foreign_policy",
+      "task_alias": "us_foreign_policy",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "us_foreign_policy",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_virology": {
+      "task": "mmlu_virology",
+      "task_alias": "virology",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "virology",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about virology.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_world_religions": {
+      "task": "mmlu_world_religions",
+      "task_alias": "world_religions",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "world_religions",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about world religions.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    }
+  },
+  "versions": {
+    "mmlu": "N/A",
+    "mmlu_abstract_algebra": 0.0,
+    "mmlu_anatomy": 0.0,
+    "mmlu_astronomy": 0.0,
+    "mmlu_business_ethics": 0.0,
+    "mmlu_clinical_knowledge": 0.0,
+    "mmlu_college_biology": 0.0,
+    "mmlu_college_chemistry": 0.0,
+    "mmlu_college_computer_science": 0.0,
+    "mmlu_college_mathematics": 0.0,
+    "mmlu_college_medicine": 0.0,
+    "mmlu_college_physics": 0.0,
+    "mmlu_computer_security": 0.0,
+    "mmlu_conceptual_physics": 0.0,
+    "mmlu_econometrics": 0.0,
+    "mmlu_electrical_engineering": 0.0,
+    "mmlu_elementary_mathematics": 0.0,
+    "mmlu_formal_logic": 0.0,
+    "mmlu_global_facts": 0.0,
+    "mmlu_high_school_biology": 0.0,
+    "mmlu_high_school_chemistry": 0.0,
+    "mmlu_high_school_computer_science": 0.0,
+    "mmlu_high_school_european_history": 0.0,
+    "mmlu_high_school_geography": 0.0,
+    "mmlu_high_school_government_and_politics": 0.0,
+    "mmlu_high_school_macroeconomics": 0.0,
+    "mmlu_high_school_mathematics": 0.0,
+    "mmlu_high_school_microeconomics": 0.0,
+    "mmlu_high_school_physics": 0.0,
+    "mmlu_high_school_psychology": 0.0,
+    "mmlu_high_school_statistics": 0.0,
+    "mmlu_high_school_us_history": 0.0,
+    "mmlu_high_school_world_history": 0.0,
+    "mmlu_human_aging": 0.0,
+    "mmlu_human_sexuality": 0.0,
+    "mmlu_humanities": "N/A",
+    "mmlu_international_law": 0.0,
+    "mmlu_jurisprudence": 0.0,
+    "mmlu_logical_fallacies": 0.0,
+    "mmlu_machine_learning": 0.0,
+    "mmlu_management": 0.0,
+    "mmlu_marketing": 0.0,
+    "mmlu_medical_genetics": 0.0,
+    "mmlu_miscellaneous": 0.0,
+    "mmlu_moral_disputes": 0.0,
+    "mmlu_moral_scenarios": 0.0,
+    "mmlu_nutrition": 0.0,
+    "mmlu_other": "N/A",
+    "mmlu_philosophy": 0.0,
+    "mmlu_prehistory": 0.0,
+    "mmlu_professional_accounting": 0.0,
+    "mmlu_professional_law": 0.0,
+    "mmlu_professional_medicine": 0.0,
+    "mmlu_professional_psychology": 0.0,
+    "mmlu_public_relations": 0.0,
+    "mmlu_security_studies": 0.0,
+    "mmlu_social_sciences": "N/A",
+    "mmlu_sociology": 0.0,
+    "mmlu_stem": "N/A",
+    "mmlu_us_foreign_policy": 0.0,
+    "mmlu_virology": 0.0,
+    "mmlu_world_religions": 0.0
+  },
+  "n-shot": {
+    "mmlu": 0,
+    "mmlu_abstract_algebra": 0,
+    "mmlu_anatomy": 0,
+    "mmlu_astronomy": 0,
+    "mmlu_business_ethics": 0,
+    "mmlu_clinical_knowledge": 0,
+    "mmlu_college_biology": 0,
+    "mmlu_college_chemistry": 0,
+    "mmlu_college_computer_science": 0,
+    "mmlu_college_mathematics": 0,
+    "mmlu_college_medicine": 0,
+    "mmlu_college_physics": 0,
+    "mmlu_computer_security": 0,
+    "mmlu_conceptual_physics": 0,
+    "mmlu_econometrics": 0,
+    "mmlu_electrical_engineering": 0,
+    "mmlu_elementary_mathematics": 0,
+    "mmlu_formal_logic": 0,
+    "mmlu_global_facts": 0,
+    "mmlu_high_school_biology": 0,
+    "mmlu_high_school_chemistry": 0,
+    "mmlu_high_school_computer_science": 0,
+    "mmlu_high_school_european_history": 0,
+    "mmlu_high_school_geography": 0,
+    "mmlu_high_school_government_and_politics": 0,
+    "mmlu_high_school_macroeconomics": 0,
+    "mmlu_high_school_mathematics": 0,
+    "mmlu_high_school_microeconomics": 0,
+    "mmlu_high_school_physics": 0,
+    "mmlu_high_school_psychology": 0,
+    "mmlu_high_school_statistics": 0,
+    "mmlu_high_school_us_history": 0,
+    "mmlu_high_school_world_history": 0,
+    "mmlu_human_aging": 0,
+    "mmlu_human_sexuality": 0,
+    "mmlu_humanities": 0,
+    "mmlu_international_law": 0,
+    "mmlu_jurisprudence": 0,
+    "mmlu_logical_fallacies": 0,
+    "mmlu_machine_learning": 0,
+    "mmlu_management": 0,
+    "mmlu_marketing": 0,
+    "mmlu_medical_genetics": 0,
+    "mmlu_miscellaneous": 0,
+    "mmlu_moral_disputes": 0,
+    "mmlu_moral_scenarios": 0,
+    "mmlu_nutrition": 0,
+    "mmlu_other": 0,
+    "mmlu_philosophy": 0,
+    "mmlu_prehistory": 0,
+    "mmlu_professional_accounting": 0,
+    "mmlu_professional_law": 0,
+    "mmlu_professional_medicine": 0,
+    "mmlu_professional_psychology": 0,
+    "mmlu_public_relations": 0,
+    "mmlu_security_studies": 0,
+    "mmlu_social_sciences": 0,
+    "mmlu_sociology": 0,
+    "mmlu_stem": 0,
+    "mmlu_us_foreign_policy": 0,
+    "mmlu_virology": 0,
+    "mmlu_world_religions": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/R4-7B-15t-No-Mask_pth,dtype=bfloat16,trust_remote_code=True",
+    "batch_size": "auto",
+    "batch_sizes": [
+      16
+    ],
+    "device": null,
+    "use_cache": null,
+    "limit": null,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": null
+  },
+  "git_hash": "8281e96"
+}

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1aeacbad31b10462e38468f9a41add94a358c97bb183815bad4bcbb2404c77f2
+size 118654

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/openbookqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,66 @@
+{
+  "results": {
+    "openbookqa": {
+      "acc,none": 0.304,
+      "acc_stderr,none": 0.02059164957122493,
+      "acc_norm,none": 0.414,
+      "acc_norm_stderr,none": 0.022049497969827865,
+      "alias": "openbookqa"
+    }
+  },
+  "configs": {
+    "openbookqa": {
+      "task": "openbookqa",
+      "dataset_path": "openbookqa",
+      "dataset_name": "main",
+      "training_split": "train",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "question_stem",
+      "doc_to_target": "{{choices.label.index(answerKey.lstrip())}}",
+      "doc_to_choice": "{{choices.text}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "acc_norm",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": true,
+      "doc_to_decontamination_query": "question_stem",
+      "metadata": {
+        "version": 1.0
+      }
+    }
+  },
+  "versions": {
+    "openbookqa": 1.0
+  },
+  "n-shot": {
+    "openbookqa": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/R4-7B-15t-No-Mask_pth,dtype=bfloat16,trust_remote_code=True",
+    "batch_size": "auto",
+    "batch_sizes": [
+      64
+    ],
+    "device": null,
+    "use_cache": null,
+    "limit": null,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": null
+  },
+  "git_hash": "8281e96"
+}

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/openbookqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4835323f43b6730c5a32cc797bcbc0fff8d451550e77a3b5179f8b1659cd8e32
+size 43388

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,283 @@
+{
+  "results": {
+    "pawsx": {
+      "acc,none": 0.4712142857142857,
+      "acc_stderr,none": 0.060879199130928825,
+      "alias": "pawsx"
+    },
+    "paws_de": {
+      "acc,none": 0.403,
+      "acc_stderr,none": 0.010970673536247517,
+      "alias": " - paws_de"
+    },
+    "paws_en": {
+      "acc,none": 0.37,
+      "acc_stderr,none": 0.01079853249993165,
+      "alias": " - paws_en"
+    },
+    "paws_es": {
+      "acc,none": 0.392,
+      "acc_stderr,none": 0.01091913979244253,
+      "alias": " - paws_es"
+    },
+    "paws_fr": {
+      "acc,none": 0.548,
+      "acc_stderr,none": 0.011131484850525779,
+      "alias": " - paws_fr"
+    },
+    "paws_ja": {
+      "acc,none": 0.543,
+      "acc_stderr,none": 0.011141704034140802,
+      "alias": " - paws_ja"
+    },
+    "paws_ko": {
+      "acc,none": 0.524,
+      "acc_stderr,none": 0.011170245619215438,
+      "alias": " - paws_ko"
+    },
+    "paws_zh": {
+      "acc,none": 0.5185,
+      "acc_stderr,none": 0.011175478542788577,
+      "alias": " - paws_zh"
+    }
+  },
+  "groups": {
+    "pawsx": {
+      "acc,none": 0.4712142857142857,
+      "acc_stderr,none": 0.060879199130928825,
+      "alias": "pawsx"
+    }
+  },
+  "configs": {
+    "paws_de": {
+      "task": "paws_de",
+      "group": "pawsx",
+      "dataset_path": "paws-x",
+      "dataset_name": "de",
+      "training_split": "train",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "",
+      "doc_to_target": "label",
+      "doc_to_choice": "{{[sentence1+\", richtig? Ja, \"+sentence2, sentence1+\", richtig? Nein, \"+sentence2]}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "paws_en": {
+      "task": "paws_en",
+      "group": "pawsx",
+      "dataset_path": "paws-x",
+      "dataset_name": "en",
+      "training_split": "train",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "",
+      "doc_to_target": "label",
+      "doc_to_choice": "{{[sentence1+\", right? Yes, \"+sentence2, sentence1+\", right? No, \"+sentence2]}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "paws_es": {
+      "task": "paws_es",
+      "group": "pawsx",
+      "dataset_path": "paws-x",
+      "dataset_name": "es",
+      "training_split": "train",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "",
+      "doc_to_target": "label",
+      "doc_to_choice": "{{[sentence1+\", verdad? Sí, \"+sentence2, sentence1+\", verdad? No, \"+sentence2]}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "paws_fr": {
+      "task": "paws_fr",
+      "group": "pawsx",
+      "dataset_path": "paws-x",
+      "dataset_name": "fr",
+      "training_split": "train",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "",
+      "doc_to_target": "label",
+      "doc_to_choice": "{{[sentence1+\", n'est-ce pas? Oui, \"+sentence2, sentence1+\", n'est-ce pas? No, \"+sentence2]}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "paws_ja": {
+      "task": "paws_ja",
+      "group": "pawsx",
+      "dataset_path": "paws-x",
+      "dataset_name": "ja",
+      "training_split": "train",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "",
+      "doc_to_target": "label",
+      "doc_to_choice": "{{[sentence1+\", ですね? はい, \"+sentence2, sentence1+\", ですね? いいえ, \"+sentence2]}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "paws_ko": {
+      "task": "paws_ko",
+      "group": "pawsx",
+      "dataset_path": "paws-x",
+      "dataset_name": "ko",
+      "training_split": "train",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "",
+      "doc_to_target": "label",
+      "doc_to_choice": "{{[sentence1+\", 맞죠? 예, \"+sentence2, sentence1+\", 맞죠? 아니요, \"+sentence2]}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "paws_zh": {
+      "task": "paws_zh",
+      "group": "pawsx",
+      "dataset_path": "paws-x",
+      "dataset_name": "zh",
+      "training_split": "train",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "",
+      "doc_to_target": "label",
+      "doc_to_choice": "{{[sentence1+\", 对吧? 是, \"+sentence2, sentence1+\", 对吧? 不是, \"+sentence2]}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    }
+  },
+  "versions": {
+    "paws_de": 0.0,
+    "paws_en": 0.0,
+    "paws_es": 0.0,
+    "paws_fr": 0.0,
+    "paws_ja": 0.0,
+    "paws_ko": 0.0,
+    "paws_zh": 0.0,
+    "pawsx": "N/A"
+  },
+  "n-shot": {
+    "paws_de": 0,
+    "paws_en": 0,
+    "paws_es": 0,
+    "paws_fr": 0,
+    "paws_ja": 0,
+    "paws_ko": 0,
+    "paws_zh": 0,
+    "pawsx": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/R4-7B-15t-No-Mask_pth,dtype=bfloat16,trust_remote_code=True",
+    "batch_size": "auto",
+    "batch_sizes": [
+      64
+    ],
+    "device": null,
+    "use_cache": null,
+    "limit": null,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": null
+  },
+  "git_hash": "8281e96"
+}

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b7ac1bbc0d95f9acf8b2a00c09e83cc57c516631bb35e21852925ede775f8ea4
+size 50070

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/piqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,64 @@
+{
+  "results": {
+    "piqa": {
+      "acc,none": 0.764961915125136,
+      "acc_stderr,none": 0.009893146688805324,
+      "acc_norm,none": 0.7747551686615887,
+      "acc_norm_stderr,none": 0.009746643471032148,
+      "alias": "piqa"
+    }
+  },
+  "configs": {
+    "piqa": {
+      "task": "piqa",
+      "dataset_path": "piqa",
+      "training_split": "train",
+      "validation_split": "validation",
+      "doc_to_text": "Question: {{goal}}\nAnswer:",
+      "doc_to_target": "label",
+      "doc_to_choice": "{{[sol1, sol2]}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "acc_norm",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": true,
+      "doc_to_decontamination_query": "goal",
+      "metadata": {
+        "version": 1.0
+      }
+    }
+  },
+  "versions": {
+    "piqa": 1.0
+  },
+  "n-shot": {
+    "piqa": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/R4-7B-15t-No-Mask_pth,dtype=bfloat16,trust_remote_code=True",
+    "batch_size": "auto",
+    "batch_sizes": [
+      64
+    ],
+    "device": null,
+    "use_cache": null,
+    "limit": null,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": null
+  },
+  "git_hash": "8281e96"
+}

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/piqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b7b3444a90fd722a1c7a63a6c27b749192774c34e3e761be19f563a7fcb2078d
+size 42150

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/sciq/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,65 @@
+{
+  "results": {
+    "sciq": {
+      "acc,none": 0.952,
+      "acc_stderr,none": 0.006763264133666682,
+      "acc_norm,none": 0.919,
+      "acc_norm_stderr,none": 0.008632121032139946,
+      "alias": "sciq"
+    }
+  },
+  "configs": {
+    "sciq": {
+      "task": "sciq",
+      "dataset_path": "sciq",
+      "training_split": "train",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "{{support.lstrip()}}\nQuestion: {{question}}\nAnswer:",
+      "doc_to_target": 3,
+      "doc_to_choice": "{{[distractor1, distractor2, distractor3, correct_answer]}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "acc_norm",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": true,
+      "doc_to_decontamination_query": "{{support}} {{question}}",
+      "metadata": {
+        "version": 1.0
+      }
+    }
+  },
+  "versions": {
+    "sciq": 1.0
+  },
+  "n-shot": {
+    "sciq": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/R4-7B-15t-No-Mask_pth,dtype=bfloat16,trust_remote_code=True",
+    "batch_size": "auto",
+    "batch_sizes": [
+      16
+    ],
+    "device": null,
+    "use_cache": null,
+    "limit": null,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": null
+  },
+  "git_hash": "8281e96"
+}

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/sciq/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8895bc6bc5b9c3db76a109263be8745d171e1b2c023a02d9b25b7ab23e4b3ea8
+size 43599

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,58 @@
+{
+  "results": {
+    "winogrande": {
+      "acc,none": 0.6748224151539068,
+      "acc_stderr,none": 0.013165525471764358,
+      "alias": "winogrande"
+    }
+  },
+  "configs": {
+    "winogrande": {
+      "task": "winogrande",
+      "dataset_path": "winogrande",
+      "dataset_name": "winogrande_xl",
+      "training_split": "train",
+      "validation_split": "validation",
+      "doc_to_text": "def doc_to_text(doc):\n    answer_to_num = {\"1\": 0, \"2\": 1}\n    return answer_to_num[doc[\"answer\"]]\n",
+      "doc_to_target": "def doc_to_target(doc):\n    idx = doc[\"sentence\"].index(\"_\") + 1\n    return doc[\"sentence\"][idx:].strip()\n",
+      "doc_to_choice": "def doc_to_choice(doc):\n    idx = doc[\"sentence\"].index(\"_\")\n    options = [doc[\"option1\"], doc[\"option2\"]]\n    return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": true,
+      "doc_to_decontamination_query": "sentence",
+      "metadata": {
+        "version": 1.0
+      }
+    }
+  },
+  "versions": {
+    "winogrande": 1.0
+  },
+  "n-shot": {
+    "winogrande": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/R4-7B-15t-No-Mask_pth,dtype=bfloat16,trust_remote_code=True",
+    "batch_size": "auto",
+    "batch_sizes": [
+      64
+    ],
+    "device": null,
+    "use_cache": null,
+    "limit": null,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": null
+  },
+  "git_hash": "8281e96"
+}

lm-eval-output/rwkv-x-dev/R4-7B-15t-No-Mask/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b3c14d782580d2dd1b7ccea691743c0a8a42c6381d2346ce3f0811b4e19af39b
+size 42933

lm-eval-output/rwkv-x-dev/R4-no-shuffle-rwkv-53/record/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,67 @@
+{
+  "results": {
+    "record": {
+      "f1,none": 0.27631047641932965,
+      "f1_stderr,none": 0.004434293873068706,
+      "em,none": 0.267,
+      "em_stderr,none": 0.004424144810664585,
+      "alias": "record"
+    }
+  },
+  "configs": {
+    "record": {
+      "task": "record",
+      "group": [
+        "super-glue-lm-eval-v1"
+      ],
+      "dataset_path": "super_glue",
+      "dataset_name": "record",
+      "training_split": "train",
+      "validation_split": "validation",
+      "doc_to_text": "def doc_to_text(doc):\n    initial_text, *highlights = doc[\"passage\"].strip().split(\"\\n@highlight\\n\")\n    text = initial_text + \"\\n\\n\"\n    for highlight in highlights:\n        text += f\"  - {highlight}.\\n\"\n    return text\n",
+      "doc_to_target": "{{answers}}",
+      "doc_to_choice": "{{entities}}",
+      "process_results": "def process_results(doc, results):\n    # ReCoRD's evaluation is actually deceptively simple:\n    # - Pick the maximum likelihood prediction entity\n    # - Evaluate the accuracy and token F1 PER EXAMPLE\n    # - Average over all examples\n    max_idx = np.argmax(np.array([result[0] for result in results]))\n\n    prediction = doc[\"entities\"][max_idx]\n    gold_label_set = doc[\"answers\"]\n    f1 = metric_max_over_ground_truths(\n        squad_metrics.compute_f1, prediction, gold_label_set\n    )\n    em = metric_max_over_ground_truths(\n        squad_metrics.compute_exact, prediction, gold_label_set\n    )\n\n    return {\n        \"f1\": f1,\n        \"em\": em,\n    }\n",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "f1",
+          "aggregation": "mean"
+        },
+        {
+          "metric": "em",
+          "higher_is_better": true,
+          "aggregation": "mean"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    }
+  },
+  "versions": {
+    "record": 1.0
+  },
+  "n-shot": {
+    "record": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/R4-no-shuffle-rwkv-53_pth,dtype=bfloat16,trust_remote_code=True",
+    "batch_size": "auto",
+    "batch_sizes": [
+      16
+    ],
+    "device": null,
+    "use_cache": null,
+    "limit": null,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": null
+  },
+  "git_hash": "8281e96"
+}

lm-eval-output/rwkv-x-dev/R4-no-shuffle-rwkv-53/record/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8885f811aa8866f500f16e1c8e6a2ece868c11c4164d2c4300c39c5fc1bfc632
+size 99307