Upload results for model Deci/DeciLM-7B
#4
by
ggbetz
- opened
data/Deci/DeciLM-7B/orig/results_24-02-03-00:47:02.json
ADDED
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{
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"results": {
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"lsat-rc_base": {
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"acc,none": 0.3420074349442379,
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"acc_stderr,none": 0.028977497019824838,
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"alias": "lsat-rc_base"
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},
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"lsat-lr_base": {
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"acc,none": 0.27058823529411763,
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"acc_stderr,none": 0.0196916426487322,
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"alias": "lsat-lr_base"
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},
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"lsat-ar_base": {
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"acc,none": 0.21739130434782608,
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"acc_stderr,none": 0.02725685083881996,
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"alias": "lsat-ar_base"
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},
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"logiqa_base": {
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"acc,none": 0.2987220447284345,
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"acc_stderr,none": 0.018307908005960646,
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"alias": "logiqa_base"
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},
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"logiqa2_base": {
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"acc,none": 0.3702290076335878,
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"acc_stderr,none": 0.012182557094147294,
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"alias": "logiqa2_base"
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}
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},
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"configs": {
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"logiqa2_base": {
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"task": "logiqa2_base",
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"group": "logikon-bench",
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"dataset_path": "logikon/logikon-bench",
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"dataset_name": "logiqa2",
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"test_split": "test",
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"doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\n \n Passage: <passage>\n \n Question: <question>\n A. <choice1>\n B. <choice2>\n C. <choice3>\n D. <choice4>\n [E. <choice5>]\n \n Answer:\n \"\"\"\n k = len(doc[\"options\"])\n choices = [\"a\", \"b\", \"c\", \"d\", \"e\"][:k]\n prompt = \"Answer the following question about the given passage.\\n\\n\"\n prompt = \"Passage: \" + doc[\"passage\"] + \"\\n\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"\\n\"\n prompt += \"Answer:\"\n return prompt\n",
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"doc_to_target": "{{answer}}",
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"doc_to_choice": "{{options}}",
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"description": "",
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"target_delimiter": " ",
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"fewshot_delimiter": "\n\n",
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"num_fewshot": 0,
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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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"logiqa_base": {
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"task": "logiqa_base",
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"group": "logikon-bench",
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"dataset_path": "logikon/logikon-bench",
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"dataset_name": "logiqa",
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"test_split": "test",
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+
"doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\n \n Passage: <passage>\n \n Question: <question>\n A. <choice1>\n B. <choice2>\n C. <choice3>\n D. <choice4>\n [E. <choice5>]\n \n Answer:\n \"\"\"\n k = len(doc[\"options\"])\n choices = [\"a\", \"b\", \"c\", \"d\", \"e\"][:k]\n prompt = \"Answer the following question about the given passage.\\n\\n\"\n prompt = \"Passage: \" + doc[\"passage\"] + \"\\n\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"\\n\"\n prompt += \"Answer:\"\n return prompt\n",
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"doc_to_target": "{{answer}}",
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"doc_to_choice": "{{options}}",
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"description": "",
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"target_delimiter": " ",
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"fewshot_delimiter": "\n\n",
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"num_fewshot": 0,
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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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"lsat-ar_base": {
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"task": "lsat-ar_base",
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"group": "logikon-bench",
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"dataset_path": "logikon/logikon-bench",
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"dataset_name": "lsat-ar",
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"test_split": "test",
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"doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\n \n Passage: <passage>\n \n Question: <question>\n A. <choice1>\n B. <choice2>\n C. <choice3>\n D. <choice4>\n [E. <choice5>]\n \n Answer:\n \"\"\"\n k = len(doc[\"options\"])\n choices = [\"a\", \"b\", \"c\", \"d\", \"e\"][:k]\n prompt = \"Answer the following question about the given passage.\\n\\n\"\n prompt = \"Passage: \" + doc[\"passage\"] + \"\\n\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"\\n\"\n prompt += \"Answer:\"\n return prompt\n",
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"doc_to_target": "{{answer}}",
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"doc_to_choice": "{{options}}",
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"description": "",
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"target_delimiter": " ",
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"fewshot_delimiter": "\n\n",
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+
"num_fewshot": 0,
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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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+
"lsat-lr_base": {
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+
"task": "lsat-lr_base",
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+
"group": "logikon-bench",
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"dataset_path": "logikon/logikon-bench",
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"dataset_name": "lsat-lr",
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+
"test_split": "test",
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"doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\n \n Passage: <passage>\n \n Question: <question>\n A. <choice1>\n B. <choice2>\n C. <choice3>\n D. <choice4>\n [E. <choice5>]\n \n Answer:\n \"\"\"\n k = len(doc[\"options\"])\n choices = [\"a\", \"b\", \"c\", \"d\", \"e\"][:k]\n prompt = \"Answer the following question about the given passage.\\n\\n\"\n prompt = \"Passage: \" + doc[\"passage\"] + \"\\n\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"\\n\"\n prompt += \"Answer:\"\n return prompt\n",
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"doc_to_target": "{{answer}}",
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"doc_to_choice": "{{options}}",
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+
"description": "",
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+
"target_delimiter": " ",
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+
"fewshot_delimiter": "\n\n",
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+
"num_fewshot": 0,
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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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+
"lsat-rc_base": {
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+
"task": "lsat-rc_base",
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+
"group": "logikon-bench",
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+
"dataset_path": "logikon/logikon-bench",
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+
"dataset_name": "lsat-rc",
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+
"test_split": "test",
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+
"doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\n \n Passage: <passage>\n \n Question: <question>\n A. <choice1>\n B. <choice2>\n C. <choice3>\n D. <choice4>\n [E. <choice5>]\n \n Answer:\n \"\"\"\n k = len(doc[\"options\"])\n choices = [\"a\", \"b\", \"c\", \"d\", \"e\"][:k]\n prompt = \"Answer the following question about the given passage.\\n\\n\"\n prompt = \"Passage: \" + doc[\"passage\"] + \"\\n\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"\\n\"\n prompt += \"Answer:\"\n return prompt\n",
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"doc_to_target": "{{answer}}",
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"doc_to_choice": "{{options}}",
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+
"description": "",
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+
"target_delimiter": " ",
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+
"fewshot_delimiter": "\n\n",
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+
"num_fewshot": 0,
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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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},
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"versions": {
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+
"logiqa2_base": 0.0,
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+
"logiqa_base": 0.0,
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+
"lsat-ar_base": 0.0,
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+
"lsat-lr_base": 0.0,
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"lsat-rc_base": 0.0
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},
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"n-shot": {
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"logiqa2_base": 0,
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"logiqa_base": 0,
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+
"lsat-ar_base": 0,
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+
"lsat-lr_base": 0,
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"lsat-rc_base": 0
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},
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"config": {
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"model": "vllm",
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"model_args": "pretrained=Deci/DeciLM-7B,revision=main,dtype=auto,tensor_parallel_size=1,gpu_memory_utilization=0.9,trust_remote_code=true,max_length=4096",
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"batch_size": "auto",
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"batch_sizes": [],
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"device": null,
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"use_cache": null,
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"limit": null,
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"bootstrap_iters": 100000,
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"gen_kwargs": null
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},
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"git_hash": "5044cf9"
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}
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