wip test

lm-eval-output/rwkv-x-dev/blink4-final/ai2_arc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,132 @@
+{
+  "results": {
+    "ai2_arc": {
+      "acc,none": 0.6344419391206315,
+      "acc_stderr,none": 0.10516305296088242,
+      "acc_norm,none": 0.6279594137542277,
+      "acc_norm_stderr,none": 0.09417167433128285,
+      "alias": "ai2_arc"
+    },
+    "arc_challenge": {
+      "acc,none": 0.4121160409556314,
+      "acc_stderr,none": 0.014383915302225398,
+      "acc_norm,none": 0.42918088737201365,
+      "acc_norm_stderr,none": 0.014464085894870653,
+      "alias": " - arc_challenge"
+    },
+    "arc_easy": {
+      "acc,none": 0.7441077441077442,
+      "acc_stderr,none": 0.008953950243013993,
+      "acc_norm,none": 0.726010101010101,
+      "acc_norm_stderr,none": 0.009151805901544026,
+      "alias": " - arc_easy"
+    }
+  },
+  "groups": {
+    "ai2_arc": {
+      "acc,none": 0.6344419391206315,
+      "acc_stderr,none": 0.10516305296088242,
+      "acc_norm,none": 0.6279594137542277,
+      "acc_norm_stderr,none": 0.09417167433128285,
+      "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/blink4-final_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/blink4-final/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 sha256:2af8132c503dc2be54a0e2969f916898fe32598701cab86c85cc24abe3cd1053
+size 21371

lm-eval-output/rwkv-x-dev/blink4-final/anli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,161 @@
+{
+  "results": {
+    "anli": {
+      "acc,none": 0.355,
+      "acc_stderr,none": 0.01991587930845683,
+      "alias": "anli"
+    },
+    "anli_r1": {
+      "acc,none": 0.384,
+      "acc_stderr,none": 0.015387682761897068,
+      "alias": " - anli_r1"
+    },
+    "anli_r2": {
+      "acc,none": 0.339,
+      "acc_stderr,none": 0.014976758771620342,
+      "alias": " - anli_r2"
+    },
+    "anli_r3": {
+      "acc,none": 0.3441666666666667,
+      "acc_stderr,none": 0.013720551062295756,
+      "alias": " - anli_r3"
+    }
+  },
+  "groups": {
+    "anli": {
+      "acc,none": 0.355,
+      "acc_stderr,none": 0.01991587930845683,
+      "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/blink4-final_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/blink4-final/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:f3f53f8dc7dd6e0f4a794fba4f61809f4c781754d0776416b0c8a879d26ec250
+size 42479

lm-eval-output/rwkv-x-dev/blink4-final/blimp/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,2249 @@
+{
+  "results": {
+    "blimp": {
+      "acc,none": 0.838134328358209,
+      "acc_stderr,none": 0.14450814442672488,
+      "alias": "blimp"
+    },
+    "blimp_adjunct_island": {
+      "acc,none": 0.913,
+      "acc_stderr,none": 0.008916866630745908,
+      "alias": " - blimp_adjunct_island"
+    },
+    "blimp_anaphor_gender_agreement": {
+      "acc,none": 0.983,
+      "acc_stderr,none": 0.004089954489689103,
+      "alias": " - blimp_anaphor_gender_agreement"
+    },
+    "blimp_anaphor_number_agreement": {
+      "acc,none": 0.999,
+      "acc_stderr,none": 0.0010000000000000074,
+      "alias": " - blimp_anaphor_number_agreement"
+    },
+    "blimp_animate_subject_passive": {
+      "acc,none": 0.83,
+      "acc_stderr,none": 0.011884495834541669,
+      "alias": " - blimp_animate_subject_passive"
+    },
+    "blimp_animate_subject_trans": {
+      "acc,none": 0.89,
+      "acc_stderr,none": 0.00989939381972443,
+      "alias": " - blimp_animate_subject_trans"
+    },
+    "blimp_causative": {
+      "acc,none": 0.786,
+      "acc_stderr,none": 0.012975838021968776,
+      "alias": " - blimp_causative"
+    },
+    "blimp_complex_NP_island": {
+      "acc,none": 0.602,
+      "acc_stderr,none": 0.015486634102858915,
+      "alias": " - blimp_complex_NP_island"
+    },
+    "blimp_coordinate_structure_constraint_complex_left_branch": {
+      "acc,none": 0.777,
+      "acc_stderr,none": 0.013169830843425663,
+      "alias": " - blimp_coordinate_structure_constraint_complex_left_branch"
+    },
+    "blimp_coordinate_structure_constraint_object_extraction": {
+      "acc,none": 0.86,
+      "acc_stderr,none": 0.010978183844357801,
+      "alias": " - blimp_coordinate_structure_constraint_object_extraction"
+    },
+    "blimp_determiner_noun_agreement_1": {
+      "acc,none": 0.996,
+      "acc_stderr,none": 0.001996994739098729,
+      "alias": " - blimp_determiner_noun_agreement_1"
+    },
+    "blimp_determiner_noun_agreement_2": {
+      "acc,none": 0.989,
+      "acc_stderr,none": 0.0032999833166078166,
+      "alias": " - blimp_determiner_noun_agreement_2"
+    },
+    "blimp_determiner_noun_agreement_irregular_1": {
+      "acc,none": 0.959,
+      "acc_stderr,none": 0.0062736240211187415,
+      "alias": " - blimp_determiner_noun_agreement_irregular_1"
+    },
+    "blimp_determiner_noun_agreement_irregular_2": {
+      "acc,none": 0.961,
+      "acc_stderr,none": 0.006125072776426122,
+      "alias": " - blimp_determiner_noun_agreement_irregular_2"
+    },
+    "blimp_determiner_noun_agreement_with_adj_2": {
+      "acc,none": 0.964,
+      "acc_stderr,none": 0.005893957816165556,
+      "alias": " - blimp_determiner_noun_agreement_with_adj_2"
+    },
+    "blimp_determiner_noun_agreement_with_adj_irregular_1": {
+      "acc,none": 0.927,
+      "acc_stderr,none": 0.008230354715244078,
+      "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": 0.983,
+      "acc_stderr,none": 0.004089954489689075,
+      "alias": " - blimp_determiner_noun_agreement_with_adjective_1"
+    },
+    "blimp_distractor_agreement_relational_noun": {
+      "acc,none": 0.934,
+      "acc_stderr,none": 0.007855297938697589,
+      "alias": " - blimp_distractor_agreement_relational_noun"
+    },
+    "blimp_distractor_agreement_relative_clause": {
+      "acc,none": 0.792,
+      "acc_stderr,none": 0.012841374572096918,
+      "alias": " - blimp_distractor_agreement_relative_clause"
+    },
+    "blimp_drop_argument": {
+      "acc,none": 0.76,
+      "acc_stderr,none": 0.013512312258920831,
+      "alias": " - blimp_drop_argument"
+    },
+    "blimp_ellipsis_n_bar_1": {
+      "acc,none": 0.779,
+      "acc_stderr,none": 0.013127502859696244,
+      "alias": " - blimp_ellipsis_n_bar_1"
+    },
+    "blimp_ellipsis_n_bar_2": {
+      "acc,none": 0.938,
+      "acc_stderr,none": 0.007629823996280309,
+      "alias": " - blimp_ellipsis_n_bar_2"
+    },
+    "blimp_existential_there_object_raising": {
+      "acc,none": 0.852,
+      "acc_stderr,none": 0.011234866364235254,
+      "alias": " - blimp_existential_there_object_raising"
+    },
+    "blimp_existential_there_quantifiers_1": {
+      "acc,none": 0.98,
+      "acc_stderr,none": 0.004429403980178343,
+      "alias": " - blimp_existential_there_quantifiers_1"
+    },
+    "blimp_existential_there_quantifiers_2": {
+      "acc,none": 0.4,
+      "acc_stderr,none": 0.015499685165842596,
+      "alias": " - blimp_existential_there_quantifiers_2"
+    },
+    "blimp_existential_there_subject_raising": {
+      "acc,none": 0.881,
+      "acc_stderr,none": 0.01024421514533666,
+      "alias": " - blimp_existential_there_subject_raising"
+    },
+    "blimp_expletive_it_object_raising": {
+      "acc,none": 0.797,
+      "acc_stderr,none": 0.012726073744598276,
+      "alias": " - blimp_expletive_it_object_raising"
+    },
+    "blimp_inchoative": {
+      "acc,none": 0.683,
+      "acc_stderr,none": 0.014721675438880219,
+      "alias": " - blimp_inchoative"
+    },
+    "blimp_intransitive": {
+      "acc,none": 0.838,
+      "acc_stderr,none": 0.01165726777130442,
+      "alias": " - blimp_intransitive"
+    },
+    "blimp_irregular_past_participle_adjectives": {
+      "acc,none": 0.925,
+      "acc_stderr,none": 0.008333333333333363,
+      "alias": " - blimp_irregular_past_participle_adjectives"
+    },
+    "blimp_irregular_past_participle_verbs": {
+      "acc,none": 0.928,
+      "acc_stderr,none": 0.008178195576218681,
+      "alias": " - blimp_irregular_past_participle_verbs"
+    },
+    "blimp_irregular_plural_subject_verb_agreement_1": {
+      "acc,none": 0.938,
+      "acc_stderr,none": 0.0076298239962803065,
+      "alias": " - blimp_irregular_plural_subject_verb_agreement_1"
+    },
+    "blimp_irregular_plural_subject_verb_agreement_2": {
+      "acc,none": 0.905,
+      "acc_stderr,none": 0.009276910103103312,
+      "alias": " - blimp_irregular_plural_subject_verb_agreement_2"
+    },
+    "blimp_left_branch_island_echo_question": {
+      "acc,none": 0.614,
+      "acc_stderr,none": 0.015402637476784359,
+      "alias": " - blimp_left_branch_island_echo_question"
+    },
+    "blimp_left_branch_island_simple_question": {
+      "acc,none": 0.879,
+      "acc_stderr,none": 0.010318210380946102,
+      "alias": " - blimp_left_branch_island_simple_question"
+    },
+    "blimp_matrix_question_npi_licensor_present": {
+      "acc,none": 0.524,
+      "acc_stderr,none": 0.015801065586651758,
+      "alias": " - blimp_matrix_question_npi_licensor_present"
+    },
+    "blimp_npi_present_1": {
+      "acc,none": 0.604,
+      "acc_stderr,none": 0.015473313265859408,
+      "alias": " - blimp_npi_present_1"
+    },
+    "blimp_npi_present_2": {
+      "acc,none": 0.699,
+      "acc_stderr,none": 0.014512395033543143,
+      "alias": " - blimp_npi_present_2"
+    },
+    "blimp_only_npi_licensor_present": {
+      "acc,none": 0.912,
+      "acc_stderr,none": 0.00896305396259208,
+      "alias": " - blimp_only_npi_licensor_present"
+    },
+    "blimp_only_npi_scope": {
+      "acc,none": 0.866,
+      "acc_stderr,none": 0.010777762298369678,
+      "alias": " - blimp_only_npi_scope"
+    },
+    "blimp_passive_1": {
+      "acc,none": 0.889,
+      "acc_stderr,none": 0.009938701010583726,
+      "alias": " - blimp_passive_1"
+    },
+    "blimp_passive_2": {
+      "acc,none": 0.903,
+      "acc_stderr,none": 0.00936368937324811,
+      "alias": " - blimp_passive_2"
+    },
+    "blimp_principle_A_c_command": {
+      "acc,none": 0.807,
+      "acc_stderr,none": 0.012486268734370148,
+      "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": 0.959,
+      "acc_stderr,none": 0.006273624021118753,
+      "alias": " - blimp_principle_A_case_2"
+    },
+    "blimp_principle_A_domain_1": {
+      "acc,none": 0.997,
+      "acc_stderr,none": 0.0017303161543469406,
+      "alias": " - blimp_principle_A_domain_1"
+    },
+    "blimp_principle_A_domain_2": {
+      "acc,none": 0.925,
+      "acc_stderr,none": 0.008333333333333347,
+      "alias": " - blimp_principle_A_domain_2"
+    },
+    "blimp_principle_A_domain_3": {
+      "acc,none": 0.804,
+      "acc_stderr,none": 0.012559527926707371,
+      "alias": " - blimp_principle_A_domain_3"
+    },
+    "blimp_principle_A_reconstruction": {
+      "acc,none": 0.529,
+      "acc_stderr,none": 0.0157926694516289,
+      "alias": " - blimp_principle_A_reconstruction"
+    },
+    "blimp_regular_plural_subject_verb_agreement_1": {
+      "acc,none": 0.97,
+      "acc_stderr,none": 0.005397140829099171,
+      "alias": " - blimp_regular_plural_subject_verb_agreement_1"
+    },
+    "blimp_regular_plural_subject_verb_agreement_2": {
+      "acc,none": 0.915,
+      "acc_stderr,none": 0.008823426366942328,
+      "alias": " - blimp_regular_plural_subject_verb_agreement_2"
+    },
+    "blimp_sentential_negation_npi_licensor_present": {
+      "acc,none": 0.987,
+      "acc_stderr,none": 0.003583830889403623,
+      "alias": " - blimp_sentential_negation_npi_licensor_present"
+    },
+    "blimp_sentential_negation_npi_scope": {
+      "acc,none": 0.741,
+      "acc_stderr,none": 0.013860415257527911,
+      "alias": " - blimp_sentential_negation_npi_scope"
+    },
+    "blimp_sentential_subject_island": {
+      "acc,none": 0.482,
+      "acc_stderr,none": 0.015809045699406728,
+      "alias": " - blimp_sentential_subject_island"
+    },
+    "blimp_superlative_quantifiers_1": {
+      "acc,none": 0.868,
+      "acc_stderr,none": 0.010709373963528012,
+      "alias": " - blimp_superlative_quantifiers_1"
+    },
+    "blimp_superlative_quantifiers_2": {
+      "acc,none": 0.977,
+      "acc_stderr,none": 0.004742730594656796,
+      "alias": " - blimp_superlative_quantifiers_2"
+    },
+    "blimp_tough_vs_raising_1": {
+      "acc,none": 0.635,
+      "acc_stderr,none": 0.015231776226264902,
+      "alias": " - blimp_tough_vs_raising_1"
+    },
+    "blimp_tough_vs_raising_2": {
+      "acc,none": 0.86,
+      "acc_stderr,none": 0.010978183844357794,
+      "alias": " - blimp_tough_vs_raising_2"
+    },
+    "blimp_transitive": {
+      "acc,none": 0.895,
+      "acc_stderr,none": 0.009698921026024942,
+      "alias": " - blimp_transitive"
+    },
+    "blimp_wh_island": {
+      "acc,none": 0.81,
+      "acc_stderr,none": 0.012411851354816324,
+      "alias": " - blimp_wh_island"
+    },
+    "blimp_wh_questions_object_gap": {
+      "acc,none": 0.862,
+      "acc_stderr,none": 0.01091215263250441,
+      "alias": " - blimp_wh_questions_object_gap"
+    },
+    "blimp_wh_questions_subject_gap": {
+      "acc,none": 0.94,
+      "acc_stderr,none": 0.007513751157474919,
+      "alias": " - blimp_wh_questions_subject_gap"
+    },
+    "blimp_wh_questions_subject_gap_long_distance": {
+      "acc,none": 0.933,
+      "acc_stderr,none": 0.007910345983177546,
+      "alias": " - blimp_wh_questions_subject_gap_long_distance"
+    },
+    "blimp_wh_vs_that_no_gap": {
+      "acc,none": 0.981,
+      "acc_stderr,none": 0.004319451082910622,
+      "alias": " - blimp_wh_vs_that_no_gap"
+    },
+    "blimp_wh_vs_that_no_gap_long_distance": {
+      "acc,none": 0.971,
+      "acc_stderr,none": 0.005309160685756978,
+      "alias": " - blimp_wh_vs_that_no_gap_long_distance"
+    },
+    "blimp_wh_vs_that_with_gap": {
+      "acc,none": 0.389,
+      "acc_stderr,none": 0.015424555647308495,
+      "alias": " - blimp_wh_vs_that_with_gap"
+    },
+    "blimp_wh_vs_that_with_gap_long_distance": {
+      "acc,none": 0.347,
+      "acc_stderr,none": 0.015060472031706622,
+      "alias": " - blimp_wh_vs_that_with_gap_long_distance"
+    }
+  },
+  "groups": {
+    "blimp": {
+      "acc,none": 0.838134328358209,
+      "acc_stderr,none": 0.14450814442672488,
+      "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/blink4-final_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/blink4-final/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 sha256:07a4d6ac48df2fa70e04309daf23c8c2291a6609a3ca40ba31314bf3ced538a1
+size 210974

lm-eval-output/rwkv-x-dev/blink4-final/copa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,58 @@
+{
+  "results": {
+    "copa": {
+      "acc,none": 0.86,
+      "acc_stderr,none": 0.03487350880197771,
+      "alias": "copa"
+    }
+  },
+  "configs": {
+    "copa": {
+      "task": "copa",
+      "group": [
+        "super-glue-lm-eval-v1"
+      ],
+      "dataset_path": "super_glue",
+      "dataset_name": "copa",
+      "training_split": "train",
+      "validation_split": "validation",
+      "doc_to_text": "def doc_to_text(doc):\n    # Drop the period\n    connector = {\n        \"cause\": \"because\",\n        \"effect\": \"therefore\",\n    }[doc[\"question\"]]\n    return doc[\"premise\"].strip()[:-1] + f\" {connector}\"\n",
+      "doc_to_target": "def doc_to_target(doc):\n    correct_choice = doc[\"choice1\"] if doc[\"label\"] == 0 else doc[\"choice2\"]\n    # Connect the sentences\n    return \" \" + convert_choice(correct_choice)\n",
+      "doc_to_choice": "def doc_to_choice(doc):\n    return [\" \" + convert_choice(doc[\"choice1\"]), \" \" + convert_choice(doc[\"choice2\"])]\n",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    }
+  },
+  "versions": {
+    "copa": 1.0
+  },
+  "n-shot": {
+    "copa": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/blink4-final_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/blink4-final/copa/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 sha256:605ac91a3ca24ade8f4e6daf044ff7db0c4dec774124df9059e66e5af9985abe
+size 47328

lm-eval-output/rwkv-x-dev/blink4-final/glue/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,374 @@
+{
+  "results": {
+    "glue": {
+      "acc,none": 0.541567413053835,
+      "acc_stderr,none": 0.012686230524656401,
+      "f1,none": 0.6660840132052501,
+      "f1_stderr,none": 0.0002490572630158045,
+      "mcc,none": 0.0,
+      "mcc_stderr,none": 0.0,
+      "alias": "glue"
+    },
+    "cola": {
+      "mcc,none": 0.0,
+      "mcc_stderr,none": 0.0,
+      "alias": " - cola"
+    },
+    "mnli": {
+      "acc,none": 0.3455934793683138,
+      "acc_stderr,none": 0.004800467701748957,
+      "alias": " - mnli"
+    },
+    "mnli_mismatch": {
+      "acc,none": 0.342860048820179,
+      "acc_stderr,none": 0.0047872766872064714,
+      "alias": " - mnli_mismatch"
+    },
+    "mrpc": {
+      "acc,none": 0.7328431372549019,
+      "acc_stderr,none": 0.021932668544150206,
+      "f1,none": 0.8340943683409436,
+      "f1_stderr,none": 0.015665614274445003,
+      "alias": " - mrpc"
+    },
+    "qnli": {
+      "acc,none": 0.49569833424858134,
+      "acc_stderr,none": 0.006765160168388145,
+      "alias": " - qnli"
+    },
+    "qqp": {
+      "acc,none": 0.6336136532278012,
+      "acc_stderr,none": 0.002396268090409224,
+      "f1,none": 0.6646290384658924,
+      "f1_stderr,none": 0.00259554515528604,
+      "alias": " - qqp"
+    },
+    "rte": {
+      "acc,none": 0.631768953068592,
+      "acc_stderr,none": 0.029032524428023707,
+      "alias": " - rte"
+    },
+    "sst2": {
+      "acc,none": 0.8979357798165137,
+      "acc_stderr,none": 0.010257707759295616,
+      "alias": " - sst2"
+    },
+    "wnli": {
+      "acc,none": 0.43661971830985913,
+      "acc_stderr,none": 0.0592793555841297,
+      "alias": " - wnli"
+    }
+  },
+  "groups": {
+    "glue": {
+      "acc,none": 0.541567413053835,
+      "acc_stderr,none": 0.012686230524656401,
+      "f1,none": 0.6660840132052501,
+      "f1_stderr,none": 0.0002490572630158045,
+      "mcc,none": 0.0,
+      "mcc_stderr,none": 0.0,
+      "alias": "glue"
+    }
+  },
+  "configs": {
+    "cola": {
+      "task": "cola",
+      "group": "glue",
+      "dataset_path": "glue",
+      "dataset_name": "cola",
+      "training_split": "train",
+      "validation_split": "validation",
+      "doc_to_text": "{{sentence}}\nQuestion: Does this sentence make sense?\nAnswer:",
+      "doc_to_target": "label",
+      "doc_to_choice": [
+        "no",
+        "yes"
+      ],
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "mcc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": true,
+      "doc_to_decontamination_query": "sentence",
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "mnli": {
+      "task": "mnli",
+      "group": "glue",
+      "dataset_path": "glue",
+      "dataset_name": "mnli",
+      "training_split": "train",
+      "validation_split": "validation_matched",
+      "doc_to_text": "def doc_to_text(doc) -> str:\n    return \"{}\\nQuestion: {} True, False or Neither?\\nAnswer:\".format(\n        doc[\"premise\"],\n        doc[\"hypothesis\"].strip()\n        + (\"\" if doc[\"hypothesis\"].strip().endswith(\".\") else \".\"),\n    )\n",
+      "doc_to_target": "label",
+      "doc_to_choice": [
+        "True",
+        "Neither",
+        "False"
+      ],
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "mnli_mismatch": {
+      "task": "mnli_mismatch",
+      "group": "glue",
+      "dataset_path": "glue",
+      "dataset_name": "mnli",
+      "training_split": "train",
+      "validation_split": "validation_mismatched",
+      "doc_to_text": "def doc_to_text(doc) -> str:\n    return \"{}\\nQuestion: {} True, False or Neither?\\nAnswer:\".format(\n        doc[\"premise\"],\n        doc[\"hypothesis\"].strip()\n        + (\"\" if doc[\"hypothesis\"].strip().endswith(\".\") else \".\"),\n    )\n",
+      "doc_to_target": "label",
+      "doc_to_choice": [
+        "True",
+        "Neither",
+        "False"
+      ],
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "mrpc": {
+      "task": "mrpc",
+      "group": "glue",
+      "dataset_path": "glue",
+      "dataset_name": "mrpc",
+      "training_split": "train",
+      "validation_split": "validation",
+      "doc_to_text": "Sentence 1: {{sentence1}}\nSentence 2: {{sentence2}}\nQuestion: Do both sentences mean the same thing?\nAnswer:",
+      "doc_to_target": "label",
+      "doc_to_choice": [
+        "no",
+        "yes"
+      ],
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        },
+        {
+          "metric": "f1"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "qnli": {
+      "task": "qnli",
+      "group": "glue",
+      "dataset_path": "glue",
+      "dataset_name": "qnli",
+      "training_split": "train",
+      "validation_split": "validation",
+      "doc_to_text": "{{question}}\n{{sentence}}\nQuestion: Does this response answer the question?\nAnswer:",
+      "doc_to_target": "label",
+      "doc_to_choice": [
+        "yes",
+        "no"
+      ],
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "qqp": {
+      "task": "qqp",
+      "group": "glue",
+      "dataset_path": "glue",
+      "dataset_name": "qqp",
+      "training_split": "train",
+      "validation_split": "validation",
+      "doc_to_text": "\nSentence 1: {{question1}}\nSentence 2: {{question2}}\nAnswer:",
+      "doc_to_target": "label",
+      "doc_to_choice": [
+        "no",
+        "yes"
+      ],
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        },
+        {
+          "metric": "f1"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "rte": {
+      "task": "rte",
+      "group": "glue",
+      "dataset_path": "glue",
+      "dataset_name": "rte",
+      "training_split": "train",
+      "validation_split": "validation",
+      "doc_to_text": "{{sentence1}}\nQuestion: {{sentence2}} True or False?\nAnswer:",
+      "doc_to_target": "label",
+      "doc_to_choice": [
+        "True",
+        "False"
+      ],
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "sst2": {
+      "task": "sst2",
+      "group": "glue",
+      "dataset_path": "glue",
+      "dataset_name": "sst2",
+      "training_split": "train",
+      "validation_split": "validation",
+      "doc_to_text": "{{sentence}}\nQuestion: Is this sentence positive or negative?\nAnswer:",
+      "doc_to_target": "label",
+      "doc_to_choice": [
+        "negative",
+        "positive"
+      ],
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "wnli": {
+      "task": "wnli",
+      "group": "glue",
+      "dataset_path": "glue",
+      "dataset_name": "wnli",
+      "training_split": "train",
+      "validation_split": "validation",
+      "doc_to_text": "{{sentence1}}\nQuestion: {{sentence2}} True or False?\nAnswer:",
+      "doc_to_target": "label",
+      "doc_to_choice": [
+        "False",
+        "True"
+      ],
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 2.0
+      }
+    }
+  },
+  "versions": {
+    "cola": 1.0,
+    "glue": "N/A",
+    "mnli": 1.0,
+    "mnli_mismatch": 1.0,
+    "mrpc": 1.0,
+    "qnli": 1.0,
+    "qqp": 1.0,
+    "rte": 1.0,
+    "sst2": 1.0,
+    "wnli": 2.0
+  },
+  "n-shot": {
+    "cola": 0,
+    "glue": 0,
+    "mnli": 0,
+    "mnli_mismatch": 0,
+    "mrpc": 0,
+    "qnli": 0,
+    "qqp": 0,
+    "rte": 0,
+    "sst2": 0,
+    "wnli": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/blink4-final_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/blink4-final/glue/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 sha256:4cbaa672bbfed7c4c9b62c5b972d3382b5ea99cbc095740b8cc8fb4e8e5ec356
+size 98809

lm-eval-output/rwkv-x-dev/blink4-final/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,67 @@
+{
+  "results": {
+    "hellaswag": {
+      "acc,none": 0.5238996215893248,
+      "acc_stderr,none": 0.004984077906216102,
+      "acc_norm,none": 0.7018522206731727,
+      "acc_norm_stderr,none": 0.004565098421085229,
+      "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/blink4-final_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/blink4-final/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 sha256:4609fedf446ce89b185c172f580b5b10a8f945aeb29ec79e25072a46c643feb6
+size 48854

lm-eval-output/rwkv-x-dev/blink4-final/lambada/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,126 @@
+{
+  "results": {
+    "lambada": {
+      "perplexity,none": 3.7825564005254915,
+      "perplexity_stderr,none": 0.24176388512812,
+      "acc,none": 0.7156995924704056,
+      "acc_stderr,none": 0.017918705868328787,
+      "alias": "lambada"
+    },
+    "lambada_openai": {
+      "perplexity,none": 3.3256835188642717,
+      "perplexity_stderr,none": 0.06553884605285366,
+      "acc,none": 0.7492722685814089,
+      "acc_stderr,none": 0.006038555858387702,
+      "alias": " - lambada_openai"
+    },
+    "lambada_standard": {
+      "perplexity,none": 4.239429282186711,
+      "perplexity_stderr,none": 0.09071319955084829,
+      "acc,none": 0.6821269163594023,
+      "acc_stderr,none": 0.006487412955192986,
+      "alias": " - lambada_standard"
+    }
+  },
+  "groups": {
+    "lambada": {
+      "perplexity,none": 3.7825564005254915,
+      "perplexity_stderr,none": 0.24176388512812,
+      "acc,none": 0.7156995924704056,
+      "acc_stderr,none": 0.017918705868328787,
+      "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/blink4-final_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/blink4-final/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:f8067e1036a4a851734878db78e6670a969091a9ce15b64cba3521764fc35246
+size 51329

lm-eval-output/rwkv-x-dev/blink4-final/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,252 @@
+{
+  "results": {
+    "lambada_multilingual": {
+      "perplexity,none": 20.984209978943372,
+      "perplexity_stderr,none": 8.241857583540895,
+      "acc,none": 0.5417426741703861,
+      "acc_stderr,none": 0.08480918553874013,
+      "alias": "lambada_multilingual"
+    },
+    "lambada_openai_mt_de": {
+      "perplexity,none": 34.20000700399246,
+      "perplexity_stderr,none": 1.8957136900662221,
+      "acc,none": 0.4288763826896953,
+      "acc_stderr,none": 0.0068951417412077875,
+      "alias": " - lambada_openai_mt_de"
+    },
+    "lambada_openai_mt_en": {
+      "perplexity,none": 3.3270060483529855,
+      "perplexity_stderr,none": 0.06549650816924392,
+      "acc,none": 0.7475257131767902,
+      "acc_stderr,none": 0.006052484945314857,
+      "alias": " - lambada_openai_mt_en"
+    },
+    "lambada_openai_mt_es": {
+      "perplexity,none": 29.648969171683188,
+      "perplexity_stderr,none": 1.467511227293892,
+      "acc,none": 0.4593440714147099,
+      "acc_stderr,none": 0.006942911275397646,
+      "alias": " - lambada_openai_mt_es"
+    },
+    "lambada_openai_mt_fr": {
+      "perplexity,none": 16.29615579933966,
+      "perplexity_stderr,none": 0.7906458936470977,
+      "acc,none": 0.5526877547059965,
+      "acc_stderr,none": 0.0069271945939575275,
+      "alias": " - lambada_openai_mt_fr"
+    },
+    "lambada_openai_mt_it": {
+      "perplexity,none": 21.448911871348567,
+      "perplexity_stderr,none": 1.134315447110098,
+      "acc,none": 0.520279448864739,
+      "acc_stderr,none": 0.006960245698059409,
+      "alias": " - lambada_openai_mt_it"
+    }
+  },
+  "groups": {
+    "lambada_multilingual": {
+      "perplexity,none": 20.984209978943372,
+      "perplexity_stderr,none": 8.241857583540895,
+      "acc,none": 0.5417426741703861,
+      "acc_stderr,none": 0.08480918553874013,
+      "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/blink4-final_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/blink4-final/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 sha256:2189f7c10f849b842c7b19c469760c75e25b71d016940f53ef2d5a62a71fa8bc
+size 39061

lm-eval-output/rwkv-x-dev/blink4-final/logiqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,66 @@
+{
+  "results": {
+    "logiqa": {
+      "acc,none": 0.2534562211981567,
+      "acc_stderr,none": 0.017061705439785736,
+      "acc_norm,none": 0.2764976958525346,
+      "acc_norm_stderr,none": 0.017543209075825194,
+      "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/blink4-final_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/blink4-final/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 sha256:829bd4eb2fcb6e089fbddfee00062cf2bc568d06b54a7272c36d26f365bf4f0c
+size 49955

lm-eval-output/rwkv-x-dev/blink4-final/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,2594 @@
+{
+  "results": {
+    "mmlu": {
+      "acc,none": 0.323885486397949,
+      "acc_stderr,none": 0.06413587939631772,
+      "alias": "mmlu"
+    },
+    "mmlu_humanities": {
+      "alias": " - humanities",
+      "acc,none": 0.31583421891604674,
+      "acc_stderr,none": 0.053843727243415865
+    },
+    "mmlu_formal_logic": {
+      "alias": "  - formal_logic",
+      "acc,none": 0.2777777777777778,
+      "acc_stderr,none": 0.040061680838488774
+    },
+    "mmlu_high_school_european_history": {
+      "alias": "  - high_school_european_history",
+      "acc,none": 0.3939393939393939,
+      "acc_stderr,none": 0.0381549430868893
+    },
+    "mmlu_high_school_us_history": {
+      "alias": "  - high_school_us_history",
+      "acc,none": 0.44607843137254904,
+      "acc_stderr,none": 0.034888454513049734
+    },
+    "mmlu_high_school_world_history": {
+      "alias": "  - high_school_world_history",
+      "acc,none": 0.4219409282700422,
+      "acc_stderr,none": 0.032148146302403695
+    },
+    "mmlu_international_law": {
+      "alias": "  - international_law",
+      "acc,none": 0.36363636363636365,
+      "acc_stderr,none": 0.043913262867240704
+    },
+    "mmlu_jurisprudence": {
+      "alias": "  - jurisprudence",
+      "acc,none": 0.3333333333333333,
+      "acc_stderr,none": 0.04557239513497752
+    },
+    "mmlu_logical_fallacies": {
+      "alias": "  - logical_fallacies",
+      "acc,none": 0.3067484662576687,
+      "acc_stderr,none": 0.036230899157241474
+    },
+    "mmlu_moral_disputes": {
+      "alias": "  - moral_disputes",
+      "acc,none": 0.33815028901734107,
+      "acc_stderr,none": 0.02546977014940017
+    },
+    "mmlu_moral_scenarios": {
+      "alias": "  - moral_scenarios",
+      "acc,none": 0.23798882681564246,
+      "acc_stderr,none": 0.014242630070574906
+    },
+    "mmlu_philosophy": {
+      "alias": "  - philosophy",
+      "acc,none": 0.38263665594855306,
+      "acc_stderr,none": 0.027604689028581996
+    },
+    "mmlu_prehistory": {
+      "alias": "  - prehistory",
+      "acc,none": 0.3549382716049383,
+      "acc_stderr,none": 0.02662415247884585
+    },
+    "mmlu_professional_law": {
+      "alias": "  - professional_law",
+      "acc,none": 0.2835723598435463,
+      "acc_stderr,none": 0.011511900775968316
+    },
+    "mmlu_world_religions": {
+      "alias": "  - world_religions",
+      "acc,none": 0.38596491228070173,
+      "acc_stderr,none": 0.03733756969066164
+    },
+    "mmlu_other": {
+      "alias": " - other",
+      "acc,none": 0.3714193756034761,
+      "acc_stderr,none": 0.05166478932586059
+    },
+    "mmlu_business_ethics": {
+      "alias": "  - business_ethics",
+      "acc,none": 0.35,
+      "acc_stderr,none": 0.0479372485441102
+    },
+    "mmlu_clinical_knowledge": {
+      "alias": "  - clinical_knowledge",
+      "acc,none": 0.4188679245283019,
+      "acc_stderr,none": 0.03036505082911521
+    },
+    "mmlu_college_medicine": {
+      "alias": "  - college_medicine",
+      "acc,none": 0.3583815028901734,
+      "acc_stderr,none": 0.03656343653353158
+    },
+    "mmlu_global_facts": {
+      "alias": "  - global_facts",
+      "acc,none": 0.35,
+      "acc_stderr,none": 0.0479372485441102
+    },
+    "mmlu_human_aging": {
+      "alias": "  - human_aging",
+      "acc,none": 0.3632286995515695,
+      "acc_stderr,none": 0.032277904428505
+    },
+    "mmlu_management": {
+      "alias": "  - management",
+      "acc,none": 0.4077669902912621,
+      "acc_stderr,none": 0.04865777570410769
+    },
+    "mmlu_marketing": {
+      "alias": "  - marketing",
+      "acc,none": 0.37606837606837606,
+      "acc_stderr,none": 0.03173393632969481
+    },
+    "mmlu_medical_genetics": {
+      "alias": "  - medical_genetics",
+      "acc,none": 0.42,
+      "acc_stderr,none": 0.049604496374885836
+    },
+    "mmlu_miscellaneous": {
+      "alias": "  - miscellaneous",
+      "acc,none": 0.42656449553001274,
+      "acc_stderr,none": 0.01768606697567564
+    },
+    "mmlu_nutrition": {
+      "alias": "  - nutrition",
+      "acc,none": 0.3104575163398693,
+      "acc_stderr,none": 0.0264930332251459
+    },
+    "mmlu_professional_accounting": {
+      "alias": "  - professional_accounting",
+      "acc,none": 0.25177304964539005,
+      "acc_stderr,none": 0.025892151156709405
+    },
+    "mmlu_professional_medicine": {
+      "alias": "  - professional_medicine",
+      "acc,none": 0.38235294117647056,
+      "acc_stderr,none": 0.02952009569768776
+    },
+    "mmlu_virology": {
+      "alias": "  - virology",
+      "acc,none": 0.3253012048192771,
+      "acc_stderr,none": 0.03647168523683227
+    },
+    "mmlu_social_sciences": {
+      "alias": " - social_sciences",
+      "acc,none": 0.34644133896652585,
+      "acc_stderr,none": 0.06350781839184878
+    },
+    "mmlu_econometrics": {
+      "alias": "  - econometrics",
+      "acc,none": 0.24561403508771928,
+      "acc_stderr,none": 0.040493392977481425
+    },
+    "mmlu_high_school_geography": {
+      "alias": "  - high_school_geography",
+      "acc,none": 0.41919191919191917,
+      "acc_stderr,none": 0.03515520728670417
+    },
+    "mmlu_high_school_government_and_politics": {
+      "alias": "  - high_school_government_and_politics",
+      "acc,none": 0.44559585492227977,
+      "acc_stderr,none": 0.03587014986075659
+    },
+    "mmlu_high_school_macroeconomics": {
+      "alias": "  - high_school_macroeconomics",
+      "acc,none": 0.3076923076923077,
+      "acc_stderr,none": 0.0234009289183105
+    },
+    "mmlu_high_school_microeconomics": {
+      "alias": "  - high_school_microeconomics",
+      "acc,none": 0.2605042016806723,
+      "acc_stderr,none": 0.028510251512341933
+    },
+    "mmlu_high_school_psychology": {
+      "alias": "  - high_school_psychology",
+      "acc,none": 0.3669724770642202,
+      "acc_stderr,none": 0.02066467565952053
+    },
+    "mmlu_human_sexuality": {
+      "alias": "  - human_sexuality",
+      "acc,none": 0.42748091603053434,
+      "acc_stderr,none": 0.04338920305792401
+    },
+    "mmlu_professional_psychology": {
+      "alias": "  - professional_psychology",
+      "acc,none": 0.31862745098039214,
+      "acc_stderr,none": 0.018850084696468705
+    },
+    "mmlu_public_relations": {
+      "alias": "  - public_relations",
+      "acc,none": 0.45454545454545453,
+      "acc_stderr,none": 0.04769300568972742
+    },
+    "mmlu_security_studies": {
+      "alias": "  - security_studies",
+      "acc,none": 0.24081632653061225,
+      "acc_stderr,none": 0.027372942201788156
+    },
+    "mmlu_sociology": {
+      "alias": "  - sociology",
+      "acc,none": 0.44776119402985076,
+      "acc_stderr,none": 0.03516184772952165
+    },
+    "mmlu_us_foreign_policy": {
+      "alias": "  - us_foreign_policy",
+      "acc,none": 0.37,
+      "acc_stderr,none": 0.04852365870939099
+    },
+    "mmlu_stem": {
+      "alias": " - stem",
+      "acc,none": 0.2670472565810339,
+      "acc_stderr,none": 0.06357982586650601
+    },
+    "mmlu_abstract_algebra": {
+      "alias": "  - abstract_algebra",
+      "acc,none": 0.17,
+      "acc_stderr,none": 0.0377525168068637
+    },
+    "mmlu_anatomy": {
+      "alias": "  - anatomy",
+      "acc,none": 0.35555555555555557,
+      "acc_stderr,none": 0.04135176749720386
+    },
+    "mmlu_astronomy": {
+      "alias": "  - astronomy",
+      "acc,none": 0.24342105263157895,
+      "acc_stderr,none": 0.034923496688842384
+    },
+    "mmlu_college_biology": {
+      "alias": "  - college_biology",
+      "acc,none": 0.3194444444444444,
+      "acc_stderr,none": 0.03899073687357335
+    },
+    "mmlu_college_chemistry": {
+      "alias": "  - college_chemistry",
+      "acc,none": 0.27,
+      "acc_stderr,none": 0.0446196043338474
+    },
+    "mmlu_college_computer_science": {
+      "alias": "  - college_computer_science",
+      "acc,none": 0.22,
+      "acc_stderr,none": 0.04163331998932268
+    },
+    "mmlu_college_mathematics": {
+      "alias": "  - college_mathematics",
+      "acc,none": 0.23,
+      "acc_stderr,none": 0.042295258468165044
+    },
+    "mmlu_college_physics": {
+      "alias": "  - college_physics",
+      "acc,none": 0.20588235294117646,
+      "acc_stderr,none": 0.04023382273617746
+    },
+    "mmlu_computer_security": {
+      "alias": "  - computer_security",
+      "acc,none": 0.34,
+      "acc_stderr,none": 0.04760952285695235
+    },
+    "mmlu_conceptual_physics": {
+      "alias": "  - conceptual_physics",
+      "acc,none": 0.3276595744680851,
+      "acc_stderr,none": 0.030683020843231008
+    },
+    "mmlu_electrical_engineering": {
+      "alias": "  - electrical_engineering",
+      "acc,none": 0.2827586206896552,
+      "acc_stderr,none": 0.03752833958003337
+    },
+    "mmlu_elementary_mathematics": {
+      "alias": "  - elementary_mathematics",
+      "acc,none": 0.21428571428571427,
+      "acc_stderr,none": 0.02113285918275443
+    },
+    "mmlu_high_school_biology": {
+      "alias": "  - high_school_biology",
+      "acc,none": 0.38064516129032255,
+      "acc_stderr,none": 0.027621717832907032
+    },
+    "mmlu_high_school_chemistry": {
+      "alias": "  - high_school_chemistry",
+      "acc,none": 0.24630541871921183,
+      "acc_stderr,none": 0.030315099285617743
+    },
+    "mmlu_high_school_computer_science": {
+      "alias": "  - high_school_computer_science",
+      "acc,none": 0.27,
+      "acc_stderr,none": 0.0446196043338474
+    },
+    "mmlu_high_school_mathematics": {
+      "alias": "  - high_school_mathematics",
+      "acc,none": 0.24074074074074073,
+      "acc_stderr,none": 0.02606715922227579
+    },
+    "mmlu_high_school_physics": {
+      "alias": "  - high_school_physics",
+      "acc,none": 0.26490066225165565,
+      "acc_stderr,none": 0.03603038545360381
+    },
+    "mmlu_high_school_statistics": {
+      "alias": "  - high_school_statistics",
+      "acc,none": 0.14814814814814814,
+      "acc_stderr,none": 0.024227629273728363
+    },
+    "mmlu_machine_learning": {
+      "alias": "  - machine_learning",
+      "acc,none": 0.32142857142857145,
+      "acc_stderr,none": 0.04432804055291517
+    }
+  },
+  "groups": {
+    "mmlu": {
+      "acc,none": 0.323885486397949,
+      "acc_stderr,none": 0.06413587939631772,
+      "alias": "mmlu"
+    },
+    "mmlu_humanities": {
+      "alias": " - humanities",
+      "acc,none": 0.31583421891604674,
+      "acc_stderr,none": 0.053843727243415865
+    },
+    "mmlu_other": {
+      "alias": " - other",
+      "acc,none": 0.3714193756034761,
+      "acc_stderr,none": 0.05166478932586059
+    },
+    "mmlu_social_sciences": {
+      "alias": " - social_sciences",
+      "acc,none": 0.34644133896652585,
+      "acc_stderr,none": 0.06350781839184878
+    },
+    "mmlu_stem": {
+      "alias": " - stem",
+      "acc,none": 0.2670472565810339,
+      "acc_stderr,none": 0.06357982586650601
+    }
+  },
+  "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/blink4-final_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/blink4-final/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 sha256:5960c3e894f10d1d1d9b28e0a4f81a6420329c8ba55e190ff0b6f265a0001871
+size 115243

lm-eval-output/rwkv-x-dev/blink4-final/openbookqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,66 @@
+{
+  "results": {
+    "openbookqa": {
+      "acc,none": 0.302,
+      "acc_stderr,none": 0.020553269174209205,
+      "acc_norm,none": 0.416,
+      "acc_norm_stderr,none": 0.02206494331392887,
+      "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/blink4-final_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/blink4-final/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 sha256:80b48a66b7c4ff83aa43f68a1c756598697a8013e6c38e07248baf98770fe846
+size 39951

lm-eval-output/rwkv-x-dev/blink4-final/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,283 @@
+{
+  "results": {
+    "pawsx": {
+      "acc,none": 0.46364285714285713,
+      "acc_stderr,none": 0.04624333088715949,
+      "alias": "pawsx"
+    },
+    "paws_de": {
+      "acc,none": 0.421,
+      "acc_stderr,none": 0.011042665902539781,
+      "alias": " - paws_de"
+    },
+    "paws_en": {
+      "acc,none": 0.3795,
+      "acc_stderr,none": 0.010853514379554391,
+      "alias": " - paws_en"
+    },
+    "paws_es": {
+      "acc,none": 0.3785,
+      "acc_stderr,none": 0.010847935926107406,
+      "alias": " - paws_es"
+    },
+    "paws_fr": {
+      "acc,none": 0.548,
+      "acc_stderr,none": 0.01113148485052578,
+      "alias": " - paws_fr"
+    },
+    "paws_ja": {
+      "acc,none": 0.531,
+      "acc_stderr,none": 0.011161621338114477,
+      "alias": " - paws_ja"
+    },
+    "paws_ko": {
+      "acc,none": 0.4815,
+      "acc_stderr,none": 0.011175478542788582,
+      "alias": " - paws_ko"
+    },
+    "paws_zh": {
+      "acc,none": 0.506,
+      "acc_stderr,none": 0.01118233080628221,
+      "alias": " - paws_zh"
+    }
+  },
+  "groups": {
+    "pawsx": {
+      "acc,none": 0.46364285714285713,
+      "acc_stderr,none": 0.04624333088715949,
+      "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/blink4-final_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/blink4-final/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:d989247861f02cf4ccf89ed0056acef26644c60ddeba7ea4749e9b5efdfea88e
+size 47739

lm-eval-output/rwkv-x-dev/blink4-final/piqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,64 @@
+{
+  "results": {
+    "piqa": {
+      "acc,none": 0.7676822633297062,
+      "acc_stderr,none": 0.009853201384168243,
+      "acc_norm,none": 0.7763873775843307,
+      "acc_norm_stderr,none": 0.00972148951917629,
+      "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/blink4-final_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/blink4-final/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 sha256:746cdb8b7f6d03ce2d22fb73194b3277b8407b4789ba4c3bc863fa0cd8933c73
+size 45545

lm-eval-output/rwkv-x-dev/blink4-final/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:ebc7563147cfa2ab33f7e822064bed5f374d1dad168d64a81db3ca805c8b3b7a
+size 427629

lm-eval-output/rwkv-x-dev/blink4-final/record/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,67 @@
+{
+  "results": {
+    "record": {
+      "f1,none": 0.28268857167363165,
+      "f1_stderr,none": 0.00446420750423061,
+      "em,none": 0.2727,
+      "em_stderr,none": 0.004453701218700751,
+      "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/blink4-final_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/blink4-final/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:eb7551bde8d1816b58dea66ea90bf59f9ecde64ae785b8b1ecbb85d1f29cfe45
+size 105121

lm-eval-output/rwkv-x-dev/blink4-final/sciq/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,65 @@
+{
+  "results": {
+    "sciq": {
+      "acc,none": 0.951,
+      "acc_stderr,none": 0.006829761756140938,
+      "acc_norm,none": 0.931,
+      "acc_norm_stderr,none": 0.00801893405031514,
+      "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/blink4-final_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/blink4-final/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:e6509632061d905c584b1c3d0c88781d112a0d40dd7361cf696040b280b11a56
+size 10452

lm-eval-output/rwkv-x-dev/blink4-final/truthfulqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,282 @@
+{
+  "results": {
+    "truthfulqa": {
+      "acc,none": 0.32668663944045867,
+      "acc_stderr,none": 0.0015161922166166773,
+      "bleu_max,none": 28.190731362000818,
+      "bleu_max_stderr,none": 0.8192896472333284,
+      "bleu_acc,none": 0.3219094247246022,
+      "bleu_acc_stderr,none": 0.0163555676119604,
+      "bleu_diff,none": -6.52307377852992,
+      "bleu_diff_stderr,none": 0.882608139760819,
+      "rouge1_max,none": 53.62870155203736,
+      "rouge1_max_stderr,none": 0.8686447297916212,
+      "rouge1_acc,none": 0.2913096695226438,
+      "rouge1_acc_stderr,none": 0.015905987048184828,
+      "rouge1_diff,none": -8.584442495314844,
+      "rouge1_diff_stderr,none": 0.9666373382314315,
+      "rouge2_max,none": 37.66322635174381,
+      "rouge2_max_stderr,none": 1.0339594500148117,
+      "rouge2_acc,none": 0.27539779681762544,
+      "rouge2_acc_stderr,none": 0.01563813566777552,
+      "rouge2_diff,none": -10.645773648157844,
+      "rouge2_diff_stderr,none": 1.1680622792150868,
+      "rougeL_max,none": 50.7677058099679,
+      "rougeL_max_stderr,none": 0.8879196339431965,
+      "rougeL_acc,none": 0.29498164014687883,
+      "rougeL_acc_stderr,none": 0.015964400965589674,
+      "rougeL_diff,none": -8.947157840870293,
+      "rougeL_diff_stderr,none": 0.9835913993380507,
+      "alias": "truthfulqa"
+    },
+    "truthfulqa_gen": {
+      "bleu_max,none": 28.190731362000818,
+      "bleu_max_stderr,none": 0.8192896472333284,
+      "bleu_acc,none": 0.3219094247246022,
+      "bleu_acc_stderr,none": 0.0163555676119604,
+      "bleu_diff,none": -6.52307377852992,
+      "bleu_diff_stderr,none": 0.882608139760819,
+      "rouge1_max,none": 53.62870155203736,
+      "rouge1_max_stderr,none": 0.8686447297916212,
+      "rouge1_acc,none": 0.2913096695226438,
+      "rouge1_acc_stderr,none": 0.015905987048184828,
+      "rouge1_diff,none": -8.584442495314844,
+      "rouge1_diff_stderr,none": 0.9666373382314315,
+      "rouge2_max,none": 37.66322635174381,
+      "rouge2_max_stderr,none": 1.0339594500148117,
+      "rouge2_acc,none": 0.27539779681762544,
+      "rouge2_acc_stderr,none": 0.01563813566777552,
+      "rouge2_diff,none": -10.645773648157844,
+      "rouge2_diff_stderr,none": 1.1680622792150868,
+      "rougeL_max,none": 50.7677058099679,
+      "rougeL_max_stderr,none": 0.8879196339431965,
+      "rougeL_acc,none": 0.29498164014687883,
+      "rougeL_acc_stderr,none": 0.015964400965589674,
+      "rougeL_diff,none": -8.947157840870293,
+      "rougeL_diff_stderr,none": 0.9835913993380507,
+      "alias": " - truthfulqa_gen"
+    },
+    "truthfulqa_mc1": {
+      "acc,none": 0.25458996328029376,
+      "acc_stderr,none": 0.015250117079156503,
+      "alias": " - truthfulqa_mc1"
+    },
+    "truthfulqa_mc2": {
+      "acc,none": 0.39878331560062363,
+      "acc_stderr,none": 0.014125370004563044,
+      "alias": " - truthfulqa_mc2"
+    }
+  },
+  "groups": {
+    "truthfulqa": {
+      "acc,none": 0.32668663944045867,
+      "acc_stderr,none": 0.0015161922166166773,
+      "bleu_max,none": 28.190731362000818,
+      "bleu_max_stderr,none": 0.8192896472333284,
+      "bleu_acc,none": 0.3219094247246022,
+      "bleu_acc_stderr,none": 0.0163555676119604,
+      "bleu_diff,none": -6.52307377852992,
+      "bleu_diff_stderr,none": 0.882608139760819,
+      "rouge1_max,none": 53.62870155203736,
+      "rouge1_max_stderr,none": 0.8686447297916212,
+      "rouge1_acc,none": 0.2913096695226438,
+      "rouge1_acc_stderr,none": 0.015905987048184828,
+      "rouge1_diff,none": -8.584442495314844,
+      "rouge1_diff_stderr,none": 0.9666373382314315,
+      "rouge2_max,none": 37.66322635174381,
+      "rouge2_max_stderr,none": 1.0339594500148117,
+      "rouge2_acc,none": 0.27539779681762544,
+      "rouge2_acc_stderr,none": 0.01563813566777552,
+      "rouge2_diff,none": -10.645773648157844,
+      "rouge2_diff_stderr,none": 1.1680622792150868,
+      "rougeL_max,none": 50.7677058099679,
+      "rougeL_max_stderr,none": 0.8879196339431965,
+      "rougeL_acc,none": 0.29498164014687883,
+      "rougeL_acc_stderr,none": 0.015964400965589674,
+      "rougeL_diff,none": -8.947157840870293,
+      "rougeL_diff_stderr,none": 0.9835913993380507,
+      "alias": "truthfulqa"
+    }
+  },
+  "configs": {
+    "truthfulqa_gen": {
+      "task": "truthfulqa_gen",
+      "group": [
+        "truthfulqa"
+      ],
+      "dataset_path": "truthful_qa",
+      "dataset_name": "generation",
+      "validation_split": "validation",
+      "process_docs": "def process_docs_gen(dataset: datasets.Dataset) -> datasets.Dataset:\n    return dataset.map(preprocess_function)\n",
+      "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question}}",
+      "doc_to_target": " ",
+      "process_results": "def process_results_gen(doc, results):\n    completion = results[0]\n    true_refs, false_refs = doc[\"correct_answers\"], doc[\"incorrect_answers\"]\n    all_refs = true_refs + false_refs\n\n    # Process the sentence-level BLEURT, BLEU, and ROUGE for similarity measures.\n\n    # # BLEURT\n    # bleurt_scores_true = self.bleurt.compute(\n    #     predictions=[completion] * len(true_refs), references=true_refs\n    # )[\"scores\"]\n    # bleurt_scores_false = self.bleurt.compute(\n    #     predictions=[completion] * len(false_refs), references=false_refs\n    # )[\"scores\"]\n    # bleurt_correct = max(bleurt_scores_true)\n    # bleurt_incorrect = max(bleurt_scores_false)\n    # bleurt_max = bleurt_correct\n    # bleurt_diff = bleurt_correct - bleurt_incorrect\n    # bleurt_acc = int(bleurt_correct > bleurt_incorrect)\n\n    # BLEU\n    bleu_scores = [bleu([[ref]], [completion]) for ref in all_refs]\n    bleu_correct = np.nanmax(bleu_scores[: len(true_refs)])\n    bleu_incorrect = np.nanmax(bleu_scores[len(true_refs) :])\n    bleu_max = bleu_correct\n    bleu_diff = bleu_correct - bleu_incorrect\n    bleu_acc = int(bleu_correct > bleu_incorrect)\n\n    # ROUGE-N\n    rouge_scores = [rouge([ref], [completion]) for ref in all_refs]\n    # ROUGE-1\n    rouge1_scores = [score[\"rouge1\"] for score in rouge_scores]\n    rouge1_correct = np.nanmax(rouge1_scores[: len(true_refs)])\n    rouge1_incorrect = np.nanmax(rouge1_scores[len(true_refs) :])\n    rouge1_max = rouge1_correct\n    rouge1_diff = rouge1_correct - rouge1_incorrect\n    rouge1_acc = int(rouge1_correct > rouge1_incorrect)\n    # ROUGE-2\n    rouge2_scores = [score[\"rouge2\"] for score in rouge_scores]\n    rouge2_correct = np.nanmax(rouge2_scores[: len(true_refs)])\n    rouge2_incorrect = np.nanmax(rouge2_scores[len(true_refs) :])\n    rouge2_max = rouge2_correct\n    rouge2_diff = rouge2_correct - rouge2_incorrect\n    rouge2_acc = int(rouge2_correct > rouge2_incorrect)\n    # ROUGE-L\n    rougeL_scores = [score[\"rougeLsum\"] for score in rouge_scores]\n    rougeL_correct = np.nanmax(rougeL_scores[: len(true_refs)])\n    rougeL_incorrect = np.nanmax(rougeL_scores[len(true_refs) :])\n    rougeL_max = rougeL_correct\n    rougeL_diff = rougeL_correct - rougeL_incorrect\n    rougeL_acc = int(rougeL_correct > rougeL_incorrect)\n\n    return {\n        # \"bleurt_max\": bleurt_max,\n        # \"bleurt_acc\": bleurt_acc,\n        # \"bleurt_diff\": bleurt_diff,\n        \"bleu_max\": bleu_max,\n        \"bleu_acc\": bleu_acc,\n        \"bleu_diff\": bleu_diff,\n        \"rouge1_max\": rouge1_max,\n        \"rouge1_acc\": rouge1_acc,\n        \"rouge1_diff\": rouge1_diff,\n        \"rouge2_max\": rouge2_max,\n        \"rouge2_acc\": rouge2_acc,\n        \"rouge2_diff\": rouge2_diff,\n        \"rougeL_max\": rougeL_max,\n        \"rougeL_acc\": rougeL_acc,\n        \"rougeL_diff\": rougeL_diff,\n    }\n",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "bleu_max",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "bleu_acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "bleu_diff",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "rouge1_max",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "rouge1_acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "rouge1_diff",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "rouge2_max",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "rouge2_acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "rouge2_diff",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "rougeL_max",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "rougeL_acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        },
+        {
+          "metric": "rougeL_diff",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "should_decontaminate": true,
+      "doc_to_decontamination_query": "question",
+      "metadata": {
+        "version": 3.0
+      }
+    },
+    "truthfulqa_mc1": {
+      "task": "truthfulqa_mc1",
+      "group": [
+        "truthfulqa"
+      ],
+      "dataset_path": "truthful_qa",
+      "dataset_name": "multiple_choice",
+      "validation_split": "validation",
+      "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}",
+      "doc_to_target": 0,
+      "doc_to_choice": "{{mc1_targets.choices}}",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": true,
+      "doc_to_decontamination_query": "question",
+      "metadata": {
+        "version": 2.0
+      }
+    },
+    "truthfulqa_mc2": {
+      "task": "truthfulqa_mc2",
+      "group": [
+        "truthfulqa"
+      ],
+      "dataset_path": "truthful_qa",
+      "dataset_name": "multiple_choice",
+      "validation_split": "validation",
+      "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}",
+      "doc_to_target": 0,
+      "doc_to_choice": "{{mc2_targets.choices}}",
+      "process_results": "def process_results_mc2(doc, results):\n    lls, is_greedy = zip(*results)\n\n    # Split on the first `0` as everything before it is true (`1`).\n    split_idx = list(doc[\"mc2_targets\"][\"labels\"]).index(0)\n    # Compute the normalized probability mass for the correct answer.\n    ll_true, ll_false = lls[:split_idx], lls[split_idx:]\n    p_true, p_false = np.exp(np.array(ll_true)), np.exp(np.array(ll_false))\n    p_true = p_true / (sum(p_true) + sum(p_false))\n\n    return {\"acc\": sum(p_true)}\n",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": true,
+      "doc_to_decontamination_query": "question",
+      "metadata": {
+        "version": 2.0
+      }
+    }
+  },
+  "versions": {
+    "truthfulqa": "N/A",
+    "truthfulqa_gen": 3.0,
+    "truthfulqa_mc1": 2.0,
+    "truthfulqa_mc2": 2.0
+  },
+  "n-shot": {
+    "truthfulqa": 0,
+    "truthfulqa_gen": 0,
+    "truthfulqa_mc1": 0,
+    "truthfulqa_mc2": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/blink4-final_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/blink4-final/truthfulqa/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 sha256:4a37d2b9f3645a8e88330154b9b1a1cf637b284cfb171c3d85bcd4c0f38210be
+size 599565

lm-eval-output/rwkv-x-dev/blink4-final/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": 0.013165525471764361,
+      "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/blink4-final_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/blink4-final/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 sha256:503271c66fcd654d4595328c9dcd37ecc0d8f9b8d6812d81a92f46aea9417072
+size 45347

lm-eval-output/rwkv-x-dev/blink4-final/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,390 @@
+{
+  "results": {
+    "xcopa": {
+      "acc,none": 0.6221818181818182,
+      "acc_stderr,none": 0.07232487995885858,
+      "alias": "xcopa"
+    },
+    "xcopa_et": {
+      "acc,none": 0.594,
+      "acc_stderr,none": 0.021983962090086333,
+      "alias": " - xcopa_et"
+    },
+    "xcopa_ht": {
+      "acc,none": 0.516,
+      "acc_stderr,none": 0.022371610982580396,
+      "alias": " - xcopa_ht"
+    },
+    "xcopa_id": {
+      "acc,none": 0.728,
+      "acc_stderr,none": 0.019920483209566055,
+      "alias": " - xcopa_id"
+    },
+    "xcopa_it": {
+      "acc,none": 0.744,
+      "acc_stderr,none": 0.019536923574747612,
+      "alias": " - xcopa_it"
+    },
+    "xcopa_qu": {
+      "acc,none": 0.512,
+      "acc_stderr,none": 0.02237662679792717,
+      "alias": " - xcopa_qu"
+    },
+    "xcopa_sw": {
+      "acc,none": 0.55,
+      "acc_stderr,none": 0.022270877485360437,
+      "alias": " - xcopa_sw"
+    },
+    "xcopa_ta": {
+      "acc,none": 0.582,
+      "acc_stderr,none": 0.022080014812228134,
+      "alias": " - xcopa_ta"
+    },
+    "xcopa_th": {
+      "acc,none": 0.58,
+      "acc_stderr,none": 0.02209471322976178,
+      "alias": " - xcopa_th"
+    },
+    "xcopa_tr": {
+      "acc,none": 0.626,
+      "acc_stderr,none": 0.021660710347204487,
+      "alias": " - xcopa_tr"
+    },
+    "xcopa_vi": {
+      "acc,none": 0.714,
+      "acc_stderr,none": 0.020229346329177514,
+      "alias": " - xcopa_vi"
+    },
+    "xcopa_zh": {
+      "acc,none": 0.698,
+      "acc_stderr,none": 0.02055326917420918,
+      "alias": " - xcopa_zh"
+    }
+  },
+  "groups": {
+    "xcopa": {
+      "acc,none": 0.6221818181818182,
+      "acc_stderr,none": 0.07232487995885858,
+      "alias": "xcopa"
+    }
+  },
+  "configs": {
+    "xcopa_et": {
+      "task": "xcopa_et",
+      "group": "xcopa",
+      "dataset_path": "xcopa",
+      "dataset_name": "et",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "functools.partial(<function doc_to_text at 0x7f3ecd1b7880>, connector={'cause': 'sest', 'effect': 'seetõttu'})",
+      "doc_to_target": "label",
+      "doc_to_choice": "def doc_to_choice(doc):\n    return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xcopa_ht": {
+      "task": "xcopa_ht",
+      "group": "xcopa",
+      "dataset_path": "xcopa",
+      "dataset_name": "ht",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "functools.partial(<function doc_to_text at 0x7f3ecd05cd60>, connector={'cause': 'poukisa', 'effect': 'donk sa'})",
+      "doc_to_target": "label",
+      "doc_to_choice": "def doc_to_choice(doc):\n    return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xcopa_id": {
+      "task": "xcopa_id",
+      "group": "xcopa",
+      "dataset_path": "xcopa",
+      "dataset_name": "id",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "functools.partial(<function doc_to_text at 0x7f3ecd237d80>, connector={'cause': 'karena', 'effect': 'maka'})",
+      "doc_to_target": "label",
+      "doc_to_choice": "def doc_to_choice(doc):\n    return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xcopa_it": {
+      "task": "xcopa_it",
+      "group": "xcopa",
+      "dataset_path": "xcopa",
+      "dataset_name": "it",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "functools.partial(<function doc_to_text at 0x7f3ecd1d8180>, connector={'cause': 'perché', 'effect': 'quindi'})",
+      "doc_to_target": "label",
+      "doc_to_choice": "def doc_to_choice(doc):\n    return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xcopa_qu": {
+      "task": "xcopa_qu",
+      "group": "xcopa",
+      "dataset_path": "xcopa",
+      "dataset_name": "qu",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "functools.partial(<function doc_to_text at 0x7f3ecd1d9120>, connector={'cause': 'imataq', 'effect': 'chaymi'})",
+      "doc_to_target": "label",
+      "doc_to_choice": "def doc_to_choice(doc):\n    return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xcopa_sw": {
+      "task": "xcopa_sw",
+      "group": "xcopa",
+      "dataset_path": "xcopa",
+      "dataset_name": "sw",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "functools.partial(<function doc_to_text at 0x7f3ecd1d8360>, connector={'cause': 'kwa sababu', 'effect': 'kwa hiyo'})",
+      "doc_to_target": "label",
+      "doc_to_choice": "def doc_to_choice(doc):\n    return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xcopa_ta": {
+      "task": "xcopa_ta",
+      "group": "xcopa",
+      "dataset_path": "xcopa",
+      "dataset_name": "ta",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "functools.partial(<function doc_to_text at 0x7f3ecd1daac0>, connector={'cause': 'காரணமாக', 'effect': 'எனவே'})",
+      "doc_to_target": "label",
+      "doc_to_choice": "def doc_to_choice(doc):\n    return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xcopa_th": {
+      "task": "xcopa_th",
+      "group": "xcopa",
+      "dataset_path": "xcopa",
+      "dataset_name": "th",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "functools.partial(<function doc_to_text at 0x7f3eccbf1080>, connector={'cause': 'เพราะ', 'effect': 'ดังนั้น'})",
+      "doc_to_target": "label",
+      "doc_to_choice": "def doc_to_choice(doc):\n    return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xcopa_tr": {
+      "task": "xcopa_tr",
+      "group": "xcopa",
+      "dataset_path": "xcopa",
+      "dataset_name": "tr",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "functools.partial(<function doc_to_text at 0x7f3eccbf1da0>, connector={'cause': 'çünkü', 'effect': 'bu yüzden'})",
+      "doc_to_target": "label",
+      "doc_to_choice": "def doc_to_choice(doc):\n    return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xcopa_vi": {
+      "task": "xcopa_vi",
+      "group": "xcopa",
+      "dataset_path": "xcopa",
+      "dataset_name": "vi",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "functools.partial(<function doc_to_text at 0x7f3eccf1c400>, connector={'cause': 'bởi vì', 'effect': 'vì vậy'})",
+      "doc_to_target": "label",
+      "doc_to_choice": "def doc_to_choice(doc):\n    return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xcopa_zh": {
+      "task": "xcopa_zh",
+      "group": "xcopa",
+      "dataset_path": "xcopa",
+      "dataset_name": "zh",
+      "validation_split": "validation",
+      "test_split": "test",
+      "doc_to_text": "functools.partial(<function doc_to_text at 0x7f3eccf1ec00>, connector={'cause': '因为', 'effect': '所以'})",
+      "doc_to_target": "label",
+      "doc_to_choice": "def doc_to_choice(doc):\n    return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+      "description": "",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "metric_list": [
+        {
+          "metric": "acc"
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 1.0
+      }
+    }
+  },
+  "versions": {
+    "xcopa": "N/A",
+    "xcopa_et": 1.0,
+    "xcopa_ht": 1.0,
+    "xcopa_id": 1.0,
+    "xcopa_it": 1.0,
+    "xcopa_qu": 1.0,
+    "xcopa_sw": 1.0,
+    "xcopa_ta": 1.0,
+    "xcopa_th": 1.0,
+    "xcopa_tr": 1.0,
+    "xcopa_vi": 1.0,
+    "xcopa_zh": 1.0
+  },
+  "n-shot": {
+    "xcopa": 0,
+    "xcopa_et": 0,
+    "xcopa_ht": 0,
+    "xcopa_id": 0,
+    "xcopa_it": 0,
+    "xcopa_qu": 0,
+    "xcopa_sw": 0,
+    "xcopa_ta": 0,
+    "xcopa_th": 0,
+    "xcopa_tr": 0,
+    "xcopa_vi": 0,
+    "xcopa_zh": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/blink4-final_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/blink4-final/xcopa/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 sha256:17eca91f33bf0506c5dbbcb017afe9d12b1ebfce7ef46beba5dbbe1245f0a535
+size 22393

lm-eval-output/rwkv-x-dev/blink4-final/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

@@ -0,0 +1,423 @@
+{
+  "results": {
+    "xstorycloze": {
+      "acc,none": 0.6323325913001624,
+      "acc_stderr,none": 0.05339216973724912,
+      "alias": "xstorycloze"
+    },
+    "xstorycloze_ar": {
+      "acc,none": 0.600264725347452,
+      "acc_stderr,none": 0.012605764077627148,
+      "alias": " - xstorycloze_ar"
+    },
+    "xstorycloze_en": {
+      "acc,none": 0.7782925215089345,
+      "acc_stderr,none": 0.010689887294959677,
+      "alias": " - xstorycloze_en"
+    },
+    "xstorycloze_es": {
+      "acc,none": 0.71409662475182,
+      "acc_stderr,none": 0.01162785634694062,
+      "alias": " - xstorycloze_es"
+    },
+    "xstorycloze_eu": {
+      "acc,none": 0.5598941098610192,
+      "acc_stderr,none": 0.01277447516071633,
+      "alias": " - xstorycloze_eu"
+    },
+    "xstorycloze_hi": {
+      "acc,none": 0.6068828590337525,
+      "acc_stderr,none": 0.01256970115195732,
+      "alias": " - xstorycloze_hi"
+    },
+    "xstorycloze_id": {
+      "acc,none": 0.6637988087359364,
+      "acc_stderr,none": 0.012157083081239747,
+      "alias": " - xstorycloze_id"
+    },
+    "xstorycloze_my": {
+      "acc,none": 0.5473196558570483,
+      "acc_stderr,none": 0.012809372866181957,
+      "alias": " - xstorycloze_my"
+    },
+    "xstorycloze_ru": {
+      "acc,none": 0.684976836532098,
+      "acc_stderr,none": 0.011954205387840951,
+      "alias": " - xstorycloze_ru"
+    },
+    "xstorycloze_sw": {
+      "acc,none": 0.5598941098610192,
+      "acc_stderr,none": 0.012774475160716323,
+      "alias": " - xstorycloze_sw"
+    },
+    "xstorycloze_te": {
+      "acc,none": 0.5936465916611515,
+      "acc_stderr,none": 0.012639429420389868,
+      "alias": " - xstorycloze_te"
+    },
+    "xstorycloze_zh": {
+      "acc,none": 0.6465916611515553,
+      "acc_stderr,none": 0.012301695486460663,
+      "alias": " - xstorycloze_zh"
+    }
+  },
+  "groups": {
+    "xstorycloze": {
+      "acc,none": 0.6323325913001624,
+      "acc_stderr,none": 0.05339216973724912,
+      "alias": "xstorycloze"
+    }
+  },
+  "configs": {
+    "xstorycloze_ar": {
+      "task": "xstorycloze_ar",
+      "group": "xstorycloze",
+      "dataset_path": "juletxara/xstory_cloze",
+      "dataset_name": "ar",
+      "training_split": "train",
+      "validation_split": "eval",
+      "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "doc_to_target": "{{answer_right_ending-1}}",
+      "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
+      "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": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xstorycloze_en": {
+      "task": "xstorycloze_en",
+      "group": "xstorycloze",
+      "dataset_path": "juletxara/xstory_cloze",
+      "dataset_name": "en",
+      "training_split": "train",
+      "validation_split": "eval",
+      "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "doc_to_target": "{{answer_right_ending-1}}",
+      "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
+      "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": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xstorycloze_es": {
+      "task": "xstorycloze_es",
+      "group": "xstorycloze",
+      "dataset_path": "juletxara/xstory_cloze",
+      "dataset_name": "es",
+      "training_split": "train",
+      "validation_split": "eval",
+      "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "doc_to_target": "{{answer_right_ending-1}}",
+      "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
+      "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": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xstorycloze_eu": {
+      "task": "xstorycloze_eu",
+      "group": "xstorycloze",
+      "dataset_path": "juletxara/xstory_cloze",
+      "dataset_name": "eu",
+      "training_split": "train",
+      "validation_split": "eval",
+      "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "doc_to_target": "{{answer_right_ending-1}}",
+      "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
+      "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": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xstorycloze_hi": {
+      "task": "xstorycloze_hi",
+      "group": "xstorycloze",
+      "dataset_path": "juletxara/xstory_cloze",
+      "dataset_name": "hi",
+      "training_split": "train",
+      "validation_split": "eval",
+      "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "doc_to_target": "{{answer_right_ending-1}}",
+      "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
+      "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": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xstorycloze_id": {
+      "task": "xstorycloze_id",
+      "group": "xstorycloze",
+      "dataset_path": "juletxara/xstory_cloze",
+      "dataset_name": "id",
+      "training_split": "train",
+      "validation_split": "eval",
+      "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "doc_to_target": "{{answer_right_ending-1}}",
+      "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
+      "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": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xstorycloze_my": {
+      "task": "xstorycloze_my",
+      "group": "xstorycloze",
+      "dataset_path": "juletxara/xstory_cloze",
+      "dataset_name": "my",
+      "training_split": "train",
+      "validation_split": "eval",
+      "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "doc_to_target": "{{answer_right_ending-1}}",
+      "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
+      "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": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xstorycloze_ru": {
+      "task": "xstorycloze_ru",
+      "group": "xstorycloze",
+      "dataset_path": "juletxara/xstory_cloze",
+      "dataset_name": "ru",
+      "training_split": "train",
+      "validation_split": "eval",
+      "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "doc_to_target": "{{answer_right_ending-1}}",
+      "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
+      "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": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xstorycloze_sw": {
+      "task": "xstorycloze_sw",
+      "group": "xstorycloze",
+      "dataset_path": "juletxara/xstory_cloze",
+      "dataset_name": "sw",
+      "training_split": "train",
+      "validation_split": "eval",
+      "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "doc_to_target": "{{answer_right_ending-1}}",
+      "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
+      "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": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xstorycloze_te": {
+      "task": "xstorycloze_te",
+      "group": "xstorycloze",
+      "dataset_path": "juletxara/xstory_cloze",
+      "dataset_name": "te",
+      "training_split": "train",
+      "validation_split": "eval",
+      "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "doc_to_target": "{{answer_right_ending-1}}",
+      "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
+      "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": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "metadata": {
+        "version": 1.0
+      }
+    },
+    "xstorycloze_zh": {
+      "task": "xstorycloze_zh",
+      "group": "xstorycloze",
+      "dataset_path": "juletxara/xstory_cloze",
+      "dataset_name": "zh",
+      "training_split": "train",
+      "validation_split": "eval",
+      "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "doc_to_target": "{{answer_right_ending-1}}",
+      "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}",
+      "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": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}",
+      "metadata": {
+        "version": 1.0
+      }
+    }
+  },
+  "versions": {
+    "xstorycloze": "N/A",
+    "xstorycloze_ar": 1.0,
+    "xstorycloze_en": 1.0,
+    "xstorycloze_es": 1.0,
+    "xstorycloze_eu": 1.0,
+    "xstorycloze_hi": 1.0,
+    "xstorycloze_id": 1.0,
+    "xstorycloze_my": 1.0,
+    "xstorycloze_ru": 1.0,
+    "xstorycloze_sw": 1.0,
+    "xstorycloze_te": 1.0,
+    "xstorycloze_zh": 1.0
+  },
+  "n-shot": {
+    "xstorycloze": 0,
+    "xstorycloze_ar": 0,
+    "xstorycloze_en": 0,
+    "xstorycloze_es": 0,
+    "xstorycloze_eu": 0,
+    "xstorycloze_hi": 0,
+    "xstorycloze_id": 0,
+    "xstorycloze_my": 0,
+    "xstorycloze_ru": 0,
+    "xstorycloze_sw": 0,
+    "xstorycloze_te": 0,
+    "xstorycloze_zh": 0
+  },
+  "config": {
+    "model": "hf",
+    "model_args": "pretrained=./rwkv-x-dev/blink4-final_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/blink4-final/xstorycloze/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:c19d529d83a073f1a761a6ca6c78762abff38e3ef80b3dec9c904d0eff398c35
+size 65210