Upload results for model allenai/tulu-2-dpo-70b

#114
data/allenai/tulu-2-dpo-70b/base/24-03-24-00:11:42.json ADDED
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+ {
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+ "results": {
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+ "alias": "eligendi-cupiditate-3313_logiqa2_base"
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+ "eligendi-cupiditate-3313_logiqa_base": {
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+ "alias": "eligendi-cupiditate-3313_logiqa_base"
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+ },
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+ },
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+ "eligendi-cupiditate-3313_lsat-lr_base": {
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+ "acc,none": 0.4980392156862745,
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+ "alias": "eligendi-cupiditate-3313_lsat-lr_base"
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+ "eligendi-cupiditate-3313_lsat-rc_base": {
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+ "alias": "eligendi-cupiditate-3313_lsat-rc_base"
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+ }
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+ },
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+ "configs": {
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+ "eligendi-cupiditate-3313_logiqa2_base": {
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+ "task": "eligendi-cupiditate-3313_logiqa2_base",
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+ "group": "logikon-bench",
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+ "dataset_path": "cot-leaderboard/cot-eval-traces",
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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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+ "group": "logikon-bench",
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+ "dataset_path": "cot-leaderboard/cot-eval-traces",
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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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+ "group": "logikon-bench",
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+ "dataset_path": "cot-leaderboard/cot-eval-traces",
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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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+ "group": "logikon-bench",
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+ "dataset_path": "cot-leaderboard/cot-eval-traces",
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+ "dataset_kwargs": {
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+ "test": "eligendi-cupiditate-3313-lsat-lr/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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+ "group": "logikon-bench",
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+ "dataset_path": "cot-leaderboard/cot-eval-traces",
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+ "dataset_kwargs": {
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+ "test": "eligendi-cupiditate-3313-lsat-rc/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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+ "config": {
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+ "model": "vllm",
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+ "model_args": "pretrained=allenai/tulu-2-dpo-70b,revision=main,dtype=bfloat16,tensor_parallel_size=8,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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+ "bootstrap_iters": 100000,
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+ },
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+ "git_hash": "a550a44"
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+ }