Update demo-leaderboard/gpt2-demo/results_2023-11-21T18-10-08.json
Browse files
demo-leaderboard/gpt2-demo/results_2023-11-21T18-10-08.json
CHANGED
@@ -57,373 +57,6 @@
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"alias": " - pubmedqa"
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}
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},
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"groups": {
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"multimedqa": {
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"alias": "stem",
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"acc_norm,none": 0.33614369501466274,
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"acc_norm_stderr,none": 0.006394243385413683,
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-
"acc,none": 0.3666430092264017,
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"acc_stderr,none": 0.005640719286996951
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-
}
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},
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"group_subtasks": {
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-
"multimedqa": [
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"mmlu_college_biology",
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"mmlu_professional_medicine",
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"mmlu_medical_genetics",
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"mmlu_college_medicine",
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"mmlu_clinical_knowledge",
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"mmlu_anatomy",
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"medqa_4options",
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"medmcqa",
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"pubmedqa"
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-
]
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},
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"configs": {
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"medmcqa": {
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"task": "medmcqa",
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"dataset_path": "medmcqa",
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"training_split": "train",
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"validation_split": "validation",
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"test_split": "validation",
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"doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Question: <question>\n Choices:\n A. <choice1>\n B. <choice2>\n C. <choice3>\n D. <choice4>\n Answer:\n \"\"\"\n choices = [doc[\"opa\"], doc[\"opb\"], doc[\"opc\"], doc[\"opd\"]]\n option_choices = {\n \"A\": choices[0],\n \"B\": choices[1],\n \"C\": choices[2],\n \"D\": choices[3],\n }\n\n prompt = \"Question: \" + doc[\"question\"] + \"\\nChoices:\\n\"\n for choice, option in option_choices.items():\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"Answer:\"\n return prompt\n",
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"doc_to_target": "cop",
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"doc_to_choice": [
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"A",
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"B",
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"C",
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"D"
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],
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"description": "",
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"target_delimiter": " ",
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"fewshot_delimiter": "\n\n",
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-
"metric_list": [
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{
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"metric": "acc",
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"aggregation": "mean",
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"higher_is_better": true
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},
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{
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"metric": "acc_norm",
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"aggregation": "mean",
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"higher_is_better": true
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}
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],
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"output_type": "multiple_choice",
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"repeats": 1,
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"should_decontaminate": true,
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"doc_to_decontamination_query": "{{question}}"
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},
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"medqa_4options": {
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"task": "medqa_4options",
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"dataset_path": "GBaker/MedQA-USMLE-4-options-hf",
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"training_split": "train",
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"validation_split": "validation",
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"test_split": "test",
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"doc_to_text": "def doc_to_text(doc) -> str:\n option_choices = {\n \"A\": doc[\"ending0\"],\n \"B\": doc[\"ending1\"],\n \"C\": doc[\"ending2\"],\n \"D\": doc[\"ending3\"],\n }\n answers = \"\".join((f\"{k}. {v}\\n\") for k, v in option_choices.items())\n return f\"Question: {doc['sent1']}\\n{answers}Answer:\"\n",
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"doc_to_target": "def doc_to_target(doc) -> int:\n return doc[\"label\"]\n",
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"doc_to_choice": [
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"A",
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"B",
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"C",
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"D"
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],
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"description": "",
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"target_delimiter": " ",
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"fewshot_delimiter": "\n\n",
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"metric_list": [
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{
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"metric": "acc",
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"aggregation": "mean",
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"higher_is_better": true
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},
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{
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"metric": "acc_norm",
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"aggregation": "mean",
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"higher_is_better": true
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}
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],
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"output_type": "multiple_choice",
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"repeats": 1,
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"should_decontaminate": false
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},
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"mmlu_anatomy": {
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"task": "mmlu_anatomy",
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"task_alias": "anatomy (mmlu)",
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"group": "multimedqa",
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"group_alias": "stem",
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"dataset_path": "hails/mmlu_no_train",
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"dataset_name": "anatomy",
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"test_split": "test",
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"fewshot_split": "dev",
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"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
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"doc_to_target": "answer",
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"doc_to_choice": [
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"A",
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"B",
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"C",
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"D"
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],
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"description": "The following are multiple choice questions (with answers) about anatomy.\n\n",
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"target_delimiter": " ",
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"fewshot_delimiter": "\n\n",
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"fewshot_config": {
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"sampler": "first_n"
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},
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"metric_list": [
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{
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"metric": "acc",
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"aggregation": "mean",
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"higher_is_better": true
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}
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],
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"output_type": "multiple_choice",
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"repeats": 1,
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"should_decontaminate": false,
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"metadata": {
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"version": 0.0
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}
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},
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"mmlu_clinical_knowledge": {
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"task": "mmlu_clinical_knowledge",
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"task_alias": "clinical_knowledge (mmlu)",
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"group": "multimedqa",
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"group_alias": "other",
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"dataset_path": "hails/mmlu_no_train",
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"dataset_name": "clinical_knowledge",
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"test_split": "test",
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"fewshot_split": "dev",
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"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
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"doc_to_target": "answer",
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"doc_to_choice": [
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"A",
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"B",
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"C",
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"D"
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],
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"description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n",
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"target_delimiter": " ",
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"fewshot_delimiter": "\n\n",
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"fewshot_config": {
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"sampler": "first_n"
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},
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"metric_list": [
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{
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"metric": "acc",
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"aggregation": "mean",
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"higher_is_better": true
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}
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],
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"output_type": "multiple_choice",
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"repeats": 1,
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"should_decontaminate": false,
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"metadata": {
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"version": 0.0
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}
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},
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"mmlu_college_biology": {
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"task": "mmlu_college_biology",
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"task_alias": "college_biology (mmlu)",
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"group": "multimedqa",
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"group_alias": "stem",
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"dataset_path": "hails/mmlu_no_train",
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"dataset_name": "college_biology",
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"test_split": "test",
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"fewshot_split": "dev",
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"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
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"doc_to_target": "answer",
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"doc_to_choice": [
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"A",
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"B",
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"C",
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"D"
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],
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"description": "The following are multiple choice questions (with answers) about college biology.\n\n",
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"target_delimiter": " ",
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"fewshot_delimiter": "\n\n",
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"fewshot_config": {
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"sampler": "first_n"
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},
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"metric_list": [
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{
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"metric": "acc",
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"aggregation": "mean",
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"higher_is_better": true
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}
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],
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"output_type": "multiple_choice",
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"repeats": 1,
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"should_decontaminate": false,
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"metadata": {
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"version": 0.0
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}
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},
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"mmlu_college_medicine": {
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"task": "mmlu_college_medicine",
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"task_alias": "college_medicine (mmlu)",
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"group": "multimedqa",
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"group_alias": "other",
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"dataset_path": "hails/mmlu_no_train",
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"dataset_name": "college_medicine",
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"test_split": "test",
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"fewshot_split": "dev",
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"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
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"doc_to_target": "answer",
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"doc_to_choice": [
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"A",
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"B",
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"C",
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"D"
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],
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"description": "The following are multiple choice questions (with answers) about college medicine.\n\n",
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"target_delimiter": " ",
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"fewshot_delimiter": "\n\n",
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"fewshot_config": {
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"sampler": "first_n"
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},
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"metric_list": [
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{
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"metric": "acc",
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"aggregation": "mean",
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"higher_is_better": true
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}
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],
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"output_type": "multiple_choice",
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"repeats": 1,
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"should_decontaminate": false,
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"metadata": {
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"version": 0.0
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}
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},
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"mmlu_medical_genetics": {
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"task": "mmlu_medical_genetics",
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"task_alias": "medical_genetics (mmlu)",
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"group": "multimedqa",
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"group_alias": "other",
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"dataset_path": "hails/mmlu_no_train",
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"dataset_name": "medical_genetics",
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"test_split": "test",
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"fewshot_split": "dev",
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"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
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"doc_to_target": "answer",
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"doc_to_choice": [
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"A",
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"B",
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"C",
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"D"
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],
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"description": "The following are multiple choice questions (with answers) about medical genetics.\n\n",
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"target_delimiter": " ",
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"fewshot_delimiter": "\n\n",
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"fewshot_config": {
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"sampler": "first_n"
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},
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"metric_list": [
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{
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"metric": "acc",
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"aggregation": "mean",
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"higher_is_better": true
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}
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],
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"output_type": "multiple_choice",
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"repeats": 1,
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"should_decontaminate": false,
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"metadata": {
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"version": 0.0
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-
}
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},
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"mmlu_professional_medicine": {
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"task": "mmlu_professional_medicine",
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"task_alias": "professional_medicine (mmlu)",
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"group": "multimedqa",
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"group_alias": "other",
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"dataset_path": "hails/mmlu_no_train",
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"dataset_name": "professional_medicine",
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"test_split": "test",
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"fewshot_split": "dev",
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"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
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"doc_to_target": "answer",
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"doc_to_choice": [
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"A",
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"B",
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"C",
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"D"
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],
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"description": "The following are multiple choice questions (with answers) about professional medicine.\n\n",
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"target_delimiter": " ",
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-
"fewshot_delimiter": "\n\n",
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"fewshot_config": {
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"sampler": "first_n"
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-
},
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"metric_list": [
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{
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"metric": "acc",
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"aggregation": "mean",
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"higher_is_better": true
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}
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],
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"output_type": "multiple_choice",
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"repeats": 1,
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"should_decontaminate": false,
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"metadata": {
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"version": 0.0
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}
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},
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"pubmedqa": {
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"task": "pubmedqa",
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"dataset_path": "bigbio/pubmed_qa",
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"dataset_name": "pubmed_qa_labeled_fold0_source",
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"training_split": "train",
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"validation_split": "validation",
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"test_split": "test",
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"doc_to_text": "def doc_to_text(doc) -> str:\n ctxs = \"\\n\".join(doc[\"CONTEXTS\"])\n return \"Abstract: {}\\nQuestion: {}\\nAnswer:\".format(\n ctxs,\n doc[\"QUESTION\"],\n )\n",
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"doc_to_target": "final_decision",
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"doc_to_choice": [
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"yes",
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"no",
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"maybe"
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],
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"description": "",
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"target_delimiter": " ",
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"fewshot_delimiter": "\n\n",
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"metric_list": [
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{
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"metric": "acc",
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"aggregation": "mean",
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"higher_is_better": true
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}
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],
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"output_type": "multiple_choice",
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"repeats": 1,
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"should_decontaminate": false,
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"metadata": {
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"version": 1.0
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}
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}
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},
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"versions": {
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"medmcqa": "Yaml",
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"medqa_4options": "Yaml",
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"mmlu_anatomy": 0.0,
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"mmlu_clinical_knowledge": 0.0,
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"mmlu_college_biology": 0.0,
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"mmlu_college_medicine": 0.0,
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-
"mmlu_medical_genetics": 0.0,
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"mmlu_professional_medicine": 0.0,
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"pubmedqa": 1.0
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},
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"n-shot": {
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"medmcqa": null,
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"medqa_4options": null,
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"mmlu_anatomy": null,
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"mmlu_clinical_knowledge": null,
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-
"mmlu_college_biology": null,
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"mmlu_college_medicine": null,
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"mmlu_medical_genetics": null,
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"mmlu_professional_medicine": null,
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"multimedqa": null,
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"pubmedqa": null
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},
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"config": {
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"model_dtype": "torch.float16",
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"model_name": "demo-leaderboard/gpt2-demo",
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"alias": " - pubmedqa"
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}
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},
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60 |
"config": {
|
61 |
"model_dtype": "torch.float16",
|
62 |
"model_name": "demo-leaderboard/gpt2-demo",
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