Upload results for model Locutusque/OpenCerebrum-1.0-7b-DPO (#194)
Browse files- Upload results for model Locutusque/OpenCerebrum-1.0-7b-DPO (a0ff32cfb8e1e41c88fd96d834f4acaf74b226c1)
data/Locutusque/OpenCerebrum-1.0-7b-DPO/base/24-04-08-13:32:26.json
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{
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"results": {
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"culpa-quibusdam-4668_logiqa2_base": {
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"acc,none": 0.3575063613231552,
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"acc_stderr,none": 0.012091723577771782,
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"alias": "culpa-quibusdam-4668_logiqa2_base"
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},
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"culpa-quibusdam-4668_logiqa_base": {
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"acc,none": 0.29233226837060705,
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"acc_stderr,none": 0.0181933664060241,
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"alias": "culpa-quibusdam-4668_logiqa_base"
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},
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"culpa-quibusdam-4668_lsat-ar_base": {
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"acc,none": 0.2,
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"acc_stderr,none": 0.026432744018203558,
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"alias": "culpa-quibusdam-4668_lsat-ar_base"
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},
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"culpa-quibusdam-4668_lsat-lr_base": {
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"acc,none": 0.2607843137254902,
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"acc_stderr,none": 0.019461101974435138,
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"alias": "culpa-quibusdam-4668_lsat-lr_base"
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},
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"culpa-quibusdam-4668_lsat-rc_base": {
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"acc,none": 0.37174721189591076,
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"acc_stderr,none": 0.029520497706913982,
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"alias": "culpa-quibusdam-4668_lsat-rc_base"
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}
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},
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"configs": {
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"culpa-quibusdam-4668_logiqa2_base": {
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"task": "culpa-quibusdam-4668_logiqa2_base",
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"group": "logikon-bench",
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"dataset_path": "cot-leaderboard/cot-eval-traces",
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"dataset_kwargs": {
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"data_files": {
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"test": "culpa-quibusdam-4668-logiqa2/test-00000-of-00001.parquet"
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}
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},
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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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"culpa-quibusdam-4668_logiqa_base": {
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"task": "culpa-quibusdam-4668_logiqa_base",
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"group": "logikon-bench",
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"dataset_path": "cot-leaderboard/cot-eval-traces",
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"dataset_kwargs": {
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"data_files": {
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"test": "culpa-quibusdam-4668-logiqa/test-00000-of-00001.parquet"
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}
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},
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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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"culpa-quibusdam-4668_lsat-ar_base": {
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"task": "culpa-quibusdam-4668_lsat-ar_base",
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"group": "logikon-bench",
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"dataset_path": "cot-leaderboard/cot-eval-traces",
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"dataset_kwargs": {
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"data_files": {
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"test": "culpa-quibusdam-4668-lsat-ar/test-00000-of-00001.parquet"
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}
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},
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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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"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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"culpa-quibusdam-4668_lsat-lr_base": {
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"task": "culpa-quibusdam-4668_lsat-lr_base",
|
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"group": "logikon-bench",
|
126 |
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"dataset_path": "cot-leaderboard/cot-eval-traces",
|
127 |
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"dataset_kwargs": {
|
128 |
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"data_files": {
|
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"test": "culpa-quibusdam-4668-lsat-lr/test-00000-of-00001.parquet"
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130 |
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}
|
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},
|
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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}}",
|
135 |
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"doc_to_choice": "{{options}}",
|
136 |
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"description": "",
|
137 |
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"target_delimiter": " ",
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"fewshot_delimiter": "\n\n",
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"num_fewshot": 0,
|
140 |
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"metric_list": [
|
141 |
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{
|
142 |
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"metric": "acc",
|
143 |
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"aggregation": "mean",
|
144 |
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"higher_is_better": true
|
145 |
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}
|
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],
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147 |
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"output_type": "multiple_choice",
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148 |
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"repeats": 1,
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"should_decontaminate": false,
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150 |
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"metadata": {
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151 |
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"version": 0.0
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152 |
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}
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153 |
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},
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154 |
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"culpa-quibusdam-4668_lsat-rc_base": {
|
155 |
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"task": "culpa-quibusdam-4668_lsat-rc_base",
|
156 |
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"group": "logikon-bench",
|
157 |
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"dataset_path": "cot-leaderboard/cot-eval-traces",
|
158 |
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"dataset_kwargs": {
|
159 |
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"data_files": {
|
160 |
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"test": "culpa-quibusdam-4668-lsat-rc/test-00000-of-00001.parquet"
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161 |
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}
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162 |
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},
|
163 |
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"test_split": "test",
|
164 |
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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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167 |
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"description": "",
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168 |
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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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171 |
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"metric_list": [
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{
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173 |
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"metric": "acc",
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174 |
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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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178 |
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"output_type": "multiple_choice",
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179 |
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"repeats": 1,
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"should_decontaminate": false,
|
181 |
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"metadata": {
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182 |
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"version": 0.0
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183 |
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}
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184 |
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}
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},
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186 |
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"versions": {
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"culpa-quibusdam-4668_logiqa2_base": 0.0,
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"culpa-quibusdam-4668_logiqa_base": 0.0,
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"culpa-quibusdam-4668_lsat-ar_base": 0.0,
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"culpa-quibusdam-4668_lsat-lr_base": 0.0,
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"culpa-quibusdam-4668_lsat-rc_base": 0.0
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},
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"n-shot": {
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"culpa-quibusdam-4668_logiqa2_base": 0,
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"culpa-quibusdam-4668_logiqa_base": 0,
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"culpa-quibusdam-4668_lsat-ar_base": 0,
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"culpa-quibusdam-4668_lsat-lr_base": 0,
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"culpa-quibusdam-4668_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=Locutusque/OpenCerebrum-1.0-7b-DPO,revision=main,dtype=bfloat16,tensor_parallel_size=1,gpu_memory_utilization=0.8,trust_remote_code=true,max_length=2048",
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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": "741db1c"
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}
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