Merge branch 'big-refactor' into cont-metrics

lm_eval/tasks/mmlu/flan_n_shot/mmlu_log_us_foreign_policy.yaml → lm_eval/tasks/mmlu/flan_n_shot/loglikelihood/mmlu_us_foreign_policy.yaml

 "dataset_name": "us_foreign_policy"
-"description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n"
+"description": "The following are multiple choice questions (with answers) about us\
+  \ foreign policy.\n\n"
+"group": "mmlu_flan_n_shot_generative_social_sciences"
 "include": "_mmlu_flan_loglikelihood_template_yaml"
-"task": "mmlu_flan_n_shot_loglikelihood_us_foreign_policy"
+"task": "mmlu_flan_n_shot_generative_us_foreign_policy"

lm_eval/tasks/mmlu/flan_n_shot/mmlu_log_virology.yaml → lm_eval/tasks/mmlu/flan_n_shot/loglikelihood/mmlu_virology.yaml

 "dataset_name": "virology"
-"description": "The following are multiple choice questions (with answers) about virology.\n\n"
+"description": "The following are multiple choice questions (with answers) about virology.\n\
+  \n"
+"group": "mmlu_flan_n_shot_generative_other"
 "include": "_mmlu_flan_loglikelihood_template_yaml"
-"task": "mmlu_flan_n_shot_loglikelihood_virology"
+"task": "mmlu_flan_n_shot_generative_virology"

lm_eval/tasks/mmlu/flan_n_shot/mmlu_log_world_religions.yaml → lm_eval/tasks/mmlu/flan_n_shot/loglikelihood/mmlu_world_religions.yaml

 "dataset_name": "world_religions"
-"description": "The following are multiple choice questions (with answers) about world religions.\n\n"
+"description": "The following are multiple choice questions (with answers) about world\
+  \ religions.\n\n"
+"group": "mmlu_flan_n_shot_generative_humanities"
 "include": "_mmlu_flan_loglikelihood_template_yaml"
-"task": "mmlu_flan_n_shot_loglikelihood_world_religions"
+"task": "mmlu_flan_n_shot_generative_world_religions"

lm_eval/tasks/pubmedqa/preprocess_pubmedqa.py

@@ -3,12 +3,3 @@ def doc_to_text(doc) -> str:
     return "Abstract: {}\nQuestion: {}\nAnswer:".format(
         ctxs, doc["QUESTION"], doc["final_decision"]
     )
-
-
-def doc_to_target(doc) -> str:
-    return " {}".format(doc["final_decision"])
-
-
-def gold_alias(doc):
-    dict_to_label = {"yes": 0, "no": 1, "maybe": 2}
-    return dict_to_label[doc["final_decision"]]