{ "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {{- messages[0].content + '\\n\\n' }}\n {%- endif %}\n {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within XML tags:\\n\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n\\n\\nFor each function call, return a json object with function name and arguments within XML tags:\\n\\n{\\\"name\\\": , \\\"arguments\\\": }\\n<|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0].role == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if message.content is string %}\n {%- set content = message.content %}\n {%- else %}\n {%- set content = '' %}\n {%- endif %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- if message.tool_calls %}\n {%- for tool_call in message.tool_calls %}\n {%- if (loop.first and content) or (not loop.first) %}\n {{- '\\n' }}\n {%- endif %}\n {%- if tool_call.function %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {%- if tool_call.arguments is string %}\n {{- tool_call.arguments }}\n {%- else %}\n {{- tool_call.arguments | tojson }}\n {%- endif %}\n {{- '}\\n' }}\n {%- endfor %}\n {%- endif %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n\\n' }}\n {{- content }}\n {{- '\\n' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}", "chat_template_sha": "64f85b198065d0fba2a81f37e10ed68161ce2c19a754c7100e67e0ca2ee9c326", "config": { "batch_size": "32", "batch_sizes": [], "bootstrap_iters": 100000, "device": "cuda:0", "fewshot_seed": 1234, "gen_kwargs": {}, "limit": null, "model": "vllm", "model_args": "pretrained=Qwen/Qwen3-4B-Instruct-2507", "numpy_seed": 1234, "random_seed": 0, "torch_seed": 1234, "use_cache": "[redacted]" }, "configs": { "mmlu_abstract_algebra": { "dataset_name": "abstract_algebra", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_abstract_algebra", "task_alias": "abstract_algebra", "test_split": "test", "unsafe_code": false }, "mmlu_anatomy": { "dataset_name": "anatomy", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about anatomy.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_anatomy", "task_alias": "anatomy", "test_split": "test", "unsafe_code": false }, "mmlu_astronomy": { "dataset_name": "astronomy", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about astronomy.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_astronomy", "task_alias": "astronomy", "test_split": "test", "unsafe_code": false }, "mmlu_business_ethics": { "dataset_name": "business_ethics", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about business ethics.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_business_ethics", "task_alias": "business_ethics", "test_split": "test", "unsafe_code": false }, "mmlu_clinical_knowledge": { "dataset_name": "clinical_knowledge", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_clinical_knowledge", "task_alias": "clinical_knowledge", "test_split": "test", "unsafe_code": false }, "mmlu_college_biology": { "dataset_name": "college_biology", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about college biology.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_college_biology", "task_alias": "college_biology", "test_split": "test", "unsafe_code": false }, "mmlu_college_chemistry": { "dataset_name": "college_chemistry", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_college_chemistry", "task_alias": "college_chemistry", "test_split": "test", "unsafe_code": false }, "mmlu_college_computer_science": { "dataset_name": "college_computer_science", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about college computer science.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_college_computer_science", "task_alias": "college_computer_science", "test_split": "test", "unsafe_code": false }, "mmlu_college_mathematics": { "dataset_name": "college_mathematics", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_college_mathematics", "task_alias": "college_mathematics", "test_split": "test", "unsafe_code": false }, "mmlu_college_medicine": { "dataset_name": "college_medicine", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about college medicine.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_college_medicine", "task_alias": "college_medicine", "test_split": "test", "unsafe_code": false }, "mmlu_college_physics": { "dataset_name": "college_physics", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about college physics.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_college_physics", "task_alias": "college_physics", "test_split": "test", "unsafe_code": false }, "mmlu_computer_security": { "dataset_name": "computer_security", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about computer security.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_computer_security", "task_alias": "computer_security", "test_split": "test", "unsafe_code": false }, "mmlu_conceptual_physics": { "dataset_name": "conceptual_physics", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_conceptual_physics", "task_alias": "conceptual_physics", "test_split": "test", "unsafe_code": false }, "mmlu_econometrics": { "dataset_name": "econometrics", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about econometrics.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_econometrics", "task_alias": "econometrics", "test_split": "test", "unsafe_code": false }, "mmlu_electrical_engineering": { "dataset_name": "electrical_engineering", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_electrical_engineering", "task_alias": "electrical_engineering", "test_split": "test", "unsafe_code": false }, "mmlu_elementary_mathematics": { "dataset_name": "elementary_mathematics", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_elementary_mathematics", "task_alias": "elementary_mathematics", "test_split": "test", "unsafe_code": false }, "mmlu_formal_logic": { "dataset_name": "formal_logic", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about formal logic.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_formal_logic", "task_alias": "formal_logic", "test_split": "test", "unsafe_code": false }, "mmlu_global_facts": { "dataset_name": "global_facts", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about global facts.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_global_facts", "task_alias": "global_facts", "test_split": "test", "unsafe_code": false }, "mmlu_high_school_biology": { "dataset_name": "high_school_biology", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about high school biology.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_high_school_biology", "task_alias": "high_school_biology", "test_split": "test", "unsafe_code": false }, "mmlu_high_school_chemistry": { "dataset_name": "high_school_chemistry", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_high_school_chemistry", "task_alias": "high_school_chemistry", "test_split": "test", "unsafe_code": false }, "mmlu_high_school_computer_science": { "dataset_name": "high_school_computer_science", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_high_school_computer_science", "task_alias": "high_school_computer_science", "test_split": "test", "unsafe_code": false }, "mmlu_high_school_european_history": { "dataset_name": "high_school_european_history", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about high school european history.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_high_school_european_history", "task_alias": "high_school_european_history", "test_split": "test", "unsafe_code": false }, "mmlu_high_school_geography": { "dataset_name": "high_school_geography", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about high school geography.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_high_school_geography", "task_alias": "high_school_geography", "test_split": "test", "unsafe_code": false }, "mmlu_high_school_government_and_politics": { "dataset_name": "high_school_government_and_politics", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_high_school_government_and_politics", "task_alias": "high_school_government_and_politics", "test_split": "test", "unsafe_code": false }, "mmlu_high_school_macroeconomics": { "dataset_name": "high_school_macroeconomics", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_high_school_macroeconomics", "task_alias": "high_school_macroeconomics", "test_split": "test", "unsafe_code": false }, "mmlu_high_school_mathematics": { "dataset_name": "high_school_mathematics", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_high_school_mathematics", "task_alias": "high_school_mathematics", "test_split": "test", "unsafe_code": false }, "mmlu_high_school_microeconomics": { "dataset_name": "high_school_microeconomics", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_high_school_microeconomics", "task_alias": "high_school_microeconomics", "test_split": "test", "unsafe_code": false }, "mmlu_high_school_physics": { "dataset_name": "high_school_physics", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about high school physics.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_high_school_physics", "task_alias": "high_school_physics", "test_split": "test", "unsafe_code": false }, "mmlu_high_school_psychology": { "dataset_name": "high_school_psychology", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_high_school_psychology", "task_alias": "high_school_psychology", "test_split": "test", "unsafe_code": false }, "mmlu_high_school_statistics": { "dataset_name": "high_school_statistics", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_high_school_statistics", "task_alias": "high_school_statistics", "test_split": "test", "unsafe_code": false }, "mmlu_high_school_us_history": { "dataset_name": "high_school_us_history", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about high school us history.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_high_school_us_history", "task_alias": "high_school_us_history", "test_split": "test", "unsafe_code": false }, "mmlu_high_school_world_history": { "dataset_name": "high_school_world_history", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about high school world history.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_high_school_world_history", "task_alias": "high_school_world_history", "test_split": "test", "unsafe_code": false }, "mmlu_human_aging": { "dataset_name": "human_aging", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about human aging.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_human_aging", "task_alias": "human_aging", "test_split": "test", "unsafe_code": false }, "mmlu_human_sexuality": { "dataset_name": "human_sexuality", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_human_sexuality", "task_alias": "human_sexuality", "test_split": "test", "unsafe_code": false }, "mmlu_international_law": { "dataset_name": "international_law", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about international law.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_international_law", "task_alias": "international_law", "test_split": "test", "unsafe_code": false }, "mmlu_jurisprudence": { "dataset_name": "jurisprudence", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_jurisprudence", "task_alias": "jurisprudence", "test_split": "test", "unsafe_code": false }, "mmlu_logical_fallacies": { "dataset_name": "logical_fallacies", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_logical_fallacies", "task_alias": "logical_fallacies", "test_split": "test", "unsafe_code": false }, "mmlu_machine_learning": { "dataset_name": "machine_learning", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about machine learning.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_machine_learning", "task_alias": "machine_learning", "test_split": "test", "unsafe_code": false }, "mmlu_management": { "dataset_name": "management", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about management.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_management", "task_alias": "management", "test_split": "test", "unsafe_code": false }, "mmlu_marketing": { "dataset_name": "marketing", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about marketing.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_marketing", "task_alias": "marketing", "test_split": "test", "unsafe_code": false }, "mmlu_medical_genetics": { "dataset_name": "medical_genetics", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_medical_genetics", "task_alias": "medical_genetics", "test_split": "test", "unsafe_code": false }, "mmlu_miscellaneous": { "dataset_name": "miscellaneous", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_miscellaneous", "task_alias": "miscellaneous", "test_split": "test", "unsafe_code": false }, "mmlu_moral_disputes": { "dataset_name": "moral_disputes", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_moral_disputes", "task_alias": "moral_disputes", "test_split": "test", "unsafe_code": false }, "mmlu_moral_scenarios": { "dataset_name": "moral_scenarios", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_moral_scenarios", "task_alias": "moral_scenarios", "test_split": "test", "unsafe_code": false }, "mmlu_nutrition": { "dataset_name": "nutrition", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about nutrition.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_nutrition", "task_alias": "nutrition", "test_split": "test", "unsafe_code": false }, "mmlu_philosophy": { "dataset_name": "philosophy", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about philosophy.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_philosophy", "task_alias": "philosophy", "test_split": "test", "unsafe_code": false }, "mmlu_prehistory": { "dataset_name": "prehistory", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about prehistory.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_prehistory", "task_alias": "prehistory", "test_split": "test", "unsafe_code": false }, "mmlu_professional_accounting": { "dataset_name": "professional_accounting", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_professional_accounting", "task_alias": "professional_accounting", "test_split": "test", "unsafe_code": false }, "mmlu_professional_law": { "dataset_name": "professional_law", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about professional law.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_professional_law", "task_alias": "professional_law", "test_split": "test", "unsafe_code": false }, "mmlu_professional_medicine": { "dataset_name": "professional_medicine", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_professional_medicine", "task_alias": "professional_medicine", "test_split": "test", "unsafe_code": false }, "mmlu_professional_psychology": { "dataset_name": "professional_psychology", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_professional_psychology", "task_alias": "professional_psychology", "test_split": "test", "unsafe_code": false }, "mmlu_public_relations": { "dataset_name": "public_relations", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about public relations.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_public_relations", "task_alias": "public_relations", "test_split": "test", "unsafe_code": false }, "mmlu_security_studies": { "dataset_name": "security_studies", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about security studies.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_security_studies", "task_alias": "security_studies", "test_split": "test", "unsafe_code": false }, "mmlu_sociology": { "dataset_name": "sociology", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about sociology.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_sociology", "task_alias": "sociology", "test_split": "test", "unsafe_code": false }, "mmlu_us_foreign_policy": { "dataset_name": "us_foreign_policy", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_us_foreign_policy", "task_alias": "us_foreign_policy", "test_split": "test", "unsafe_code": false }, "mmlu_virology": { "dataset_name": "virology", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about virology.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_virology", "task_alias": "virology", "test_split": "test", "unsafe_code": false }, "mmlu_world_religions": { "dataset_name": "world_religions", "dataset_path": "cais/mmlu", "description": "The following are multiple choice questions (with answers) about world religions.\n\n", "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_config": { "doc_to_choice": [ "A", "B", "C", "D" ], "doc_to_target": "answer", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "fewshot_delimiter": "\n\n", "fewshot_indices": null, "gen_prefix": null, "process_docs": null, "sampler": "first_n", "samples": null, "split": "dev", "target_delimiter": " " }, "fewshot_delimiter": "\n\n", "fewshot_split": "dev", "metadata": { "config_source": "[redacted]", "dtype": "bfloat16", "gpu_memory_utilization": 0.82, "pretrained": "Qwen/Qwen3-4B-Instruct-2507", "tensor_parallel_size": 1, "trust_remote_code": true, "version": 1.0 }, "metric_list": [ { "aggregation": "mean", "higher_is_better": true, "metric": "acc" } ], "num_fewshot": 0, "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "target_delimiter": " ", "task": "mmlu_world_religions", "task_alias": "world_religions", "test_split": "test", "unsafe_code": false } }, "date": 1781175138.5280895, "eot_token_id": 151645, "fewshot_as_multiturn": true, "git_hash": null, "group_subtasks": { "mmlu": [ "mmlu_stem", "mmlu_other", "mmlu_social_sciences", "mmlu_humanities" ], "mmlu_humanities": [ "mmlu_formal_logic", "mmlu_high_school_european_history", "mmlu_high_school_us_history", "mmlu_high_school_world_history", "mmlu_international_law", "mmlu_jurisprudence", "mmlu_logical_fallacies", "mmlu_moral_disputes", "mmlu_moral_scenarios", "mmlu_philosophy", "mmlu_prehistory", "mmlu_professional_law", "mmlu_world_religions" ], "mmlu_other": [ "mmlu_business_ethics", "mmlu_clinical_knowledge", "mmlu_college_medicine", "mmlu_global_facts", "mmlu_human_aging", "mmlu_management", "mmlu_marketing", "mmlu_medical_genetics", "mmlu_miscellaneous", "mmlu_nutrition", "mmlu_professional_accounting", "mmlu_professional_medicine", "mmlu_virology" ], "mmlu_social_sciences": [ "mmlu_econometrics", "mmlu_high_school_geography", "mmlu_high_school_government_and_politics", "mmlu_high_school_macroeconomics", "mmlu_high_school_microeconomics", "mmlu_high_school_psychology", "mmlu_human_sexuality", "mmlu_professional_psychology", "mmlu_public_relations", "mmlu_security_studies", "mmlu_sociology", "mmlu_us_foreign_policy" ], "mmlu_stem": [ "mmlu_abstract_algebra", "mmlu_anatomy", "mmlu_astronomy", "mmlu_college_biology", "mmlu_college_chemistry", "mmlu_college_computer_science", "mmlu_college_mathematics", "mmlu_college_physics", "mmlu_computer_security", "mmlu_conceptual_physics", "mmlu_electrical_engineering", "mmlu_elementary_mathematics", "mmlu_high_school_biology", "mmlu_high_school_chemistry", "mmlu_high_school_computer_science", "mmlu_high_school_mathematics", "mmlu_high_school_physics", "mmlu_high_school_statistics", "mmlu_machine_learning" ] }, "groups": { "mmlu": { "acc,none": 0.6189289275032047, "acc_stderr,none": 0.003746138843326914, "alias": "mmlu", "name": "mmlu", "sample_count": { "acc,none": 14042 }, "sample_len": 14042 }, "mmlu_humanities": { "acc,none": 0.5596174282678003, "acc_stderr,none": 0.00661316692569494, "alias": "humanities", "name": "mmlu_humanities", "sample_count": { "acc,none": 4705 }, "sample_len": 4705 }, "mmlu_other": { "acc,none": 0.6903765690376569, "acc_stderr,none": 0.00793504827765504, "alias": "other", "name": "mmlu_other", "sample_count": { "acc,none": 3107 }, "sample_len": 3107 }, "mmlu_social_sciences": { "acc,none": 0.7565810854728632, "acc_stderr,none": 0.007580062219729006, "alias": "social sciences", "name": "mmlu_social_sciences", "sample_count": { "acc,none": 3077 }, "sample_len": 3077 }, "mmlu_stem": { "acc,none": 0.5026958452267681, "acc_stderr,none": 0.008068176972734112, "alias": "stem", "name": "mmlu_stem", "sample_count": { "acc,none": 3153 }, "sample_len": 3153 } }, "higher_is_better": { "mmlu_abstract_algebra": { "acc": true }, "mmlu_anatomy": { "acc": true }, "mmlu_astronomy": { "acc": true }, "mmlu_business_ethics": { "acc": true }, "mmlu_clinical_knowledge": { "acc": true }, "mmlu_college_biology": { "acc": true }, "mmlu_college_chemistry": { "acc": true }, "mmlu_college_computer_science": { "acc": true }, "mmlu_college_mathematics": { "acc": true }, "mmlu_college_medicine": { "acc": true }, "mmlu_college_physics": { "acc": true }, "mmlu_computer_security": { "acc": true }, "mmlu_conceptual_physics": { "acc": true }, "mmlu_econometrics": { "acc": true }, "mmlu_electrical_engineering": { "acc": true }, "mmlu_elementary_mathematics": { "acc": true }, "mmlu_formal_logic": { "acc": true }, "mmlu_global_facts": { "acc": true }, "mmlu_high_school_biology": { "acc": true }, "mmlu_high_school_chemistry": { "acc": true }, "mmlu_high_school_computer_science": { "acc": true }, "mmlu_high_school_european_history": { "acc": true }, "mmlu_high_school_geography": { "acc": true }, "mmlu_high_school_government_and_politics": { "acc": true }, "mmlu_high_school_macroeconomics": { "acc": true }, "mmlu_high_school_mathematics": { "acc": true }, "mmlu_high_school_microeconomics": { "acc": true }, "mmlu_high_school_physics": { "acc": true }, "mmlu_high_school_psychology": { "acc": true }, "mmlu_high_school_statistics": { "acc": true }, "mmlu_high_school_us_history": { "acc": true }, "mmlu_high_school_world_history": { "acc": true }, "mmlu_human_aging": { "acc": true }, "mmlu_human_sexuality": { "acc": true }, "mmlu_humanities": { "acc": true }, "mmlu_international_law": { "acc": true }, "mmlu_jurisprudence": { "acc": true }, "mmlu_logical_fallacies": { "acc": true }, "mmlu_machine_learning": { "acc": true }, "mmlu_management": { "acc": true }, "mmlu_marketing": { "acc": true }, "mmlu_medical_genetics": { "acc": true }, "mmlu_miscellaneous": { "acc": true }, "mmlu_moral_disputes": { "acc": true }, "mmlu_moral_scenarios": { "acc": true }, "mmlu_nutrition": { "acc": true }, "mmlu_other": { "acc": true }, "mmlu_philosophy": { "acc": true }, "mmlu_prehistory": { "acc": true }, "mmlu_professional_accounting": { "acc": true }, "mmlu_professional_law": { "acc": true }, "mmlu_professional_medicine": { "acc": true }, "mmlu_professional_psychology": { "acc": true }, "mmlu_public_relations": { "acc": true }, "mmlu_security_studies": { "acc": true }, "mmlu_social_sciences": { "acc": true }, "mmlu_sociology": { "acc": true }, "mmlu_stem": { "acc": true }, "mmlu_us_foreign_policy": { "acc": true }, "mmlu_virology": { "acc": true }, "mmlu_world_religions": { "acc": true } }, "lm_eval_version": "0.4.12", "max_length": 262144, "model_name": "Qwen/Qwen3-4B-Instruct-2507", "model_name_sanitized": "Qwen/Qwen3-4B-Instruct-2507", "model_source": "Qwen/Qwen3-4B-Instruct-2507", "n-samples": { "mmlu_abstract_algebra": { "effective": 100, "original": 100 }, "mmlu_anatomy": { "effective": 135, "original": 135 }, "mmlu_astronomy": { "effective": 152, "original": 152 }, "mmlu_business_ethics": { "effective": 100, "original": 100 }, "mmlu_clinical_knowledge": { "effective": 265, "original": 265 }, "mmlu_college_biology": { "effective": 144, "original": 144 }, "mmlu_college_chemistry": { "effective": 100, "original": 100 }, "mmlu_college_computer_science": { "effective": 100, "original": 100 }, "mmlu_college_mathematics": { "effective": 100, "original": 100 }, "mmlu_college_medicine": { "effective": 173, "original": 173 }, "mmlu_college_physics": { "effective": 102, "original": 102 }, "mmlu_computer_security": { "effective": 100, "original": 100 }, "mmlu_conceptual_physics": { "effective": 235, "original": 235 }, "mmlu_econometrics": { "effective": 114, "original": 114 }, "mmlu_electrical_engineering": { "effective": 145, "original": 145 }, "mmlu_elementary_mathematics": { "effective": 378, "original": 378 }, "mmlu_formal_logic": { "effective": 126, "original": 126 }, "mmlu_global_facts": { "effective": 100, "original": 100 }, "mmlu_high_school_biology": { "effective": 310, "original": 310 }, "mmlu_high_school_chemistry": { "effective": 203, "original": 203 }, "mmlu_high_school_computer_science": { "effective": 100, "original": 100 }, "mmlu_high_school_european_history": { "effective": 165, "original": 165 }, "mmlu_high_school_geography": { "effective": 198, "original": 198 }, "mmlu_high_school_government_and_politics": { "effective": 193, "original": 193 }, "mmlu_high_school_macroeconomics": { "effective": 390, "original": 390 }, "mmlu_high_school_mathematics": { "effective": 270, "original": 270 }, "mmlu_high_school_microeconomics": { "effective": 238, "original": 238 }, "mmlu_high_school_physics": { "effective": 151, "original": 151 }, "mmlu_high_school_psychology": { "effective": 545, "original": 545 }, "mmlu_high_school_statistics": { "effective": 216, "original": 216 }, "mmlu_high_school_us_history": { "effective": 204, "original": 204 }, "mmlu_high_school_world_history": { "effective": 237, "original": 237 }, "mmlu_human_aging": { "effective": 223, "original": 223 }, "mmlu_human_sexuality": { "effective": 131, "original": 131 }, "mmlu_international_law": { "effective": 121, "original": 121 }, "mmlu_jurisprudence": { "effective": 108, "original": 108 }, "mmlu_logical_fallacies": { "effective": 163, "original": 163 }, "mmlu_machine_learning": { "effective": 112, "original": 112 }, "mmlu_management": { "effective": 103, "original": 103 }, "mmlu_marketing": { "effective": 234, "original": 234 }, "mmlu_medical_genetics": { "effective": 100, "original": 100 }, "mmlu_miscellaneous": { "effective": 783, "original": 783 }, "mmlu_moral_disputes": { "effective": 346, "original": 346 }, "mmlu_moral_scenarios": { "effective": 895, "original": 895 }, "mmlu_nutrition": { "effective": 306, "original": 306 }, "mmlu_philosophy": { "effective": 311, "original": 311 }, "mmlu_prehistory": { "effective": 324, "original": 324 }, "mmlu_professional_accounting": { "effective": 282, "original": 282 }, "mmlu_professional_law": { "effective": 1534, "original": 1534 }, "mmlu_professional_medicine": { "effective": 272, "original": 272 }, "mmlu_professional_psychology": { "effective": 612, "original": 612 }, "mmlu_public_relations": { "effective": 110, "original": 110 }, "mmlu_security_studies": { "effective": 245, "original": 245 }, "mmlu_sociology": { "effective": 201, "original": 201 }, "mmlu_us_foreign_policy": { "effective": 100, "original": 100 }, "mmlu_virology": { "effective": 166, "original": 166 }, "mmlu_world_religions": { "effective": 171, "original": 171 } }, "n-shot": { "mmlu_abstract_algebra": 0, "mmlu_anatomy": 0, "mmlu_astronomy": 0, "mmlu_business_ethics": 0, "mmlu_clinical_knowledge": 0, "mmlu_college_biology": 0, "mmlu_college_chemistry": 0, "mmlu_college_computer_science": 0, "mmlu_college_mathematics": 0, "mmlu_college_medicine": 0, "mmlu_college_physics": 0, "mmlu_computer_security": 0, "mmlu_conceptual_physics": 0, "mmlu_econometrics": 0, "mmlu_electrical_engineering": 0, "mmlu_elementary_mathematics": 0, "mmlu_formal_logic": 0, "mmlu_global_facts": 0, "mmlu_high_school_biology": 0, "mmlu_high_school_chemistry": 0, "mmlu_high_school_computer_science": 0, "mmlu_high_school_european_history": 0, "mmlu_high_school_geography": 0, "mmlu_high_school_government_and_politics": 0, "mmlu_high_school_macroeconomics": 0, "mmlu_high_school_mathematics": 0, "mmlu_high_school_microeconomics": 0, "mmlu_high_school_physics": 0, "mmlu_high_school_psychology": 0, "mmlu_high_school_statistics": 0, "mmlu_high_school_us_history": 0, "mmlu_high_school_world_history": 0, "mmlu_human_aging": 0, "mmlu_human_sexuality": 0, "mmlu_humanities": 0, "mmlu_international_law": 0, "mmlu_jurisprudence": 0, "mmlu_logical_fallacies": 0, "mmlu_machine_learning": 0, "mmlu_management": 0, "mmlu_marketing": 0, "mmlu_medical_genetics": 0, "mmlu_miscellaneous": 0, "mmlu_moral_disputes": 0, "mmlu_moral_scenarios": 0, "mmlu_nutrition": 0, "mmlu_other": 0, "mmlu_philosophy": 0, "mmlu_prehistory": 0, "mmlu_professional_accounting": 0, "mmlu_professional_law": 0, "mmlu_professional_medicine": 0, "mmlu_professional_psychology": 0, "mmlu_public_relations": 0, "mmlu_security_studies": 0, "mmlu_social_sciences": 0, "mmlu_sociology": 0, "mmlu_stem": 0, "mmlu_us_foreign_policy": 0, "mmlu_virology": 0, "mmlu_world_religions": 0 }, "results": { "mmlu": { "acc,none": 0.6189289275032047, "acc_stderr,none": 0.003746138843326914, "alias": "mmlu", "name": "mmlu", "sample_count": { "acc,none": 14042 }, "sample_len": 14042 }, "mmlu_abstract_algebra": { "acc,none": 0.23, "acc_stderr,none": 0.04229525846816507, "alias": "abstract_algebra", "name": "mmlu_abstract_algebra", "sample_len": 100 }, "mmlu_anatomy": { "acc,none": 0.6444444444444445, "acc_stderr,none": 0.04135176749720385, "alias": "anatomy", "name": "mmlu_anatomy", "sample_len": 135 }, "mmlu_astronomy": { "acc,none": 0.7828947368421053, "acc_stderr,none": 0.03355045304882924, "alias": "astronomy", "name": "mmlu_astronomy", "sample_len": 152 }, "mmlu_business_ethics": { "acc,none": 0.7, "acc_stderr,none": 0.04605661864718383, "alias": "business_ethics", "name": "mmlu_business_ethics", "sample_len": 100 }, "mmlu_clinical_knowledge": { "acc,none": 0.7584905660377359, "acc_stderr,none": 0.02634148037111831, "alias": "clinical_knowledge", "name": "mmlu_clinical_knowledge", "sample_len": 265 }, "mmlu_college_biology": { "acc,none": 0.8194444444444444, "acc_stderr,none": 0.03216600808802272, "alias": "college_biology", "name": "mmlu_college_biology", "sample_len": 144 }, "mmlu_college_chemistry": { "acc,none": 0.42, "acc_stderr,none": 0.04960449637488583, "alias": "college_chemistry", "name": "mmlu_college_chemistry", "sample_len": 100 }, "mmlu_college_computer_science": { "acc,none": 0.5, "acc_stderr,none": 0.050251890762960605, "alias": "college_computer_science", "name": "mmlu_college_computer_science", "sample_len": 100 }, "mmlu_college_mathematics": { "acc,none": 0.22, "acc_stderr,none": 0.041633319989322654, "alias": "college_mathematics", "name": "mmlu_college_mathematics", "sample_len": 100 }, "mmlu_college_medicine": { "acc,none": 0.6358381502890174, "acc_stderr,none": 0.03669072477416912, "alias": "college_medicine", "name": "mmlu_college_medicine", "sample_len": 173 }, "mmlu_college_physics": { "acc,none": 0.39215686274509803, "acc_stderr,none": 0.04858083574266346, "alias": "college_physics", "name": "mmlu_college_physics", "sample_len": 102 }, "mmlu_computer_security": { "acc,none": 0.7, "acc_stderr,none": 0.04605661864718383, "alias": "computer_security", "name": "mmlu_computer_security", "sample_len": 100 }, "mmlu_conceptual_physics": { "acc,none": 0.6808510638297872, "acc_stderr,none": 0.03047297336338012, "alias": "conceptual_physics", "name": "mmlu_conceptual_physics", "sample_len": 235 }, "mmlu_econometrics": { "acc,none": 0.5175438596491229, "acc_stderr,none": 0.04700708033551044, "alias": "econometrics", "name": "mmlu_econometrics", "sample_len": 114 }, "mmlu_electrical_engineering": { "acc,none": 0.593103448275862, "acc_stderr,none": 0.040937939812662354, "alias": "electrical_engineering", "name": "mmlu_electrical_engineering", "sample_len": 145 }, "mmlu_elementary_mathematics": { "acc,none": 0.24338624338624337, "acc_stderr,none": 0.022101128787415353, "alias": "elementary_mathematics", "name": "mmlu_elementary_mathematics", "sample_len": 378 }, "mmlu_formal_logic": { "acc,none": 0.3333333333333333, "acc_stderr,none": 0.04216370213557839, "alias": "formal_logic", "name": "mmlu_formal_logic", "sample_len": 126 }, "mmlu_global_facts": { "acc,none": 0.38, "acc_stderr,none": 0.04878317312145634, "alias": "global_facts", "name": "mmlu_global_facts", "sample_len": 100 }, "mmlu_high_school_biology": { "acc,none": 0.8161290322580645, "acc_stderr,none": 0.022037217340267787, "alias": "high_school_biology", "name": "mmlu_high_school_biology", "sample_len": 310 }, "mmlu_high_school_chemistry": { "acc,none": 0.458128078817734, "acc_stderr,none": 0.035056301407857406, "alias": "high_school_chemistry", "name": "mmlu_high_school_chemistry", "sample_len": 203 }, "mmlu_high_school_computer_science": { "acc,none": 0.69, "acc_stderr,none": 0.046482319871173176, "alias": "high_school_computer_science", "name": "mmlu_high_school_computer_science", "sample_len": 100 }, "mmlu_high_school_european_history": { "acc,none": 0.8, "acc_stderr,none": 0.031234752377721213, "alias": "high_school_european_history", "name": "mmlu_high_school_european_history", "sample_len": 165 }, "mmlu_high_school_geography": { "acc,none": 0.7929292929292929, "acc_stderr,none": 0.02886977846026699, "alias": "high_school_geography", "name": "mmlu_high_school_geography", "sample_len": 198 }, "mmlu_high_school_government_and_politics": { "acc,none": 0.8756476683937824, "acc_stderr,none": 0.02381447708659357, "alias": "high_school_government_and_politics", "name": "mmlu_high_school_government_and_politics", "sample_len": 193 }, "mmlu_high_school_macroeconomics": { "acc,none": 0.6615384615384615, "acc_stderr,none": 0.023991500500313064, "alias": "high_school_macroeconomics", "name": "mmlu_high_school_macroeconomics", "sample_len": 390 }, "mmlu_high_school_mathematics": { "acc,none": 0.2111111111111111, "acc_stderr,none": 0.02488211685765511, "alias": "high_school_mathematics", "name": "mmlu_high_school_mathematics", "sample_len": 270 }, "mmlu_high_school_microeconomics": { "acc,none": 0.7857142857142857, "acc_stderr,none": 0.026653531596715505, "alias": "high_school_microeconomics", "name": "mmlu_high_school_microeconomics", "sample_len": 238 }, "mmlu_high_school_physics": { "acc,none": 0.3841059602649007, "acc_stderr,none": 0.03971301814719192, "alias": "high_school_physics", "name": "mmlu_high_school_physics", "sample_len": 151 }, "mmlu_high_school_psychology": { "acc,none": 0.8660550458715597, "acc_stderr,none": 0.014602811435592633, "alias": "high_school_psychology", "name": "mmlu_high_school_psychology", "sample_len": 545 }, "mmlu_high_school_statistics": { "acc,none": 0.4537037037037037, "acc_stderr,none": 0.033953227263757976, "alias": "high_school_statistics", "name": "mmlu_high_school_statistics", "sample_len": 216 }, "mmlu_high_school_us_history": { "acc,none": 0.8284313725490197, "acc_stderr,none": 0.026460569561240675, "alias": "high_school_us_history", "name": "mmlu_high_school_us_history", "sample_len": 204 }, "mmlu_high_school_world_history": { "acc,none": 0.8270042194092827, "acc_stderr,none": 0.024621562866768382, "alias": "high_school_world_history", "name": "mmlu_high_school_world_history", "sample_len": 237 }, "mmlu_human_aging": { "acc,none": 0.6367713004484304, "acc_stderr,none": 0.03227790442850494, "alias": "human_aging", "name": "mmlu_human_aging", "sample_len": 223 }, "mmlu_human_sexuality": { "acc,none": 0.732824427480916, "acc_stderr,none": 0.03880848301082397, "alias": "human_sexuality", "name": "mmlu_human_sexuality", "sample_len": 131 }, "mmlu_humanities": { "acc,none": 0.5596174282678003, "acc_stderr,none": 0.00661316692569494, "alias": "humanities", "name": "mmlu_humanities", "sample_count": { "acc,none": 4705 }, "sample_len": 4705 }, "mmlu_international_law": { "acc,none": 0.8347107438016529, "acc_stderr,none": 0.03390780612972774, "alias": "international_law", "name": "mmlu_international_law", "sample_len": 121 }, "mmlu_jurisprudence": { "acc,none": 0.7407407407407407, "acc_stderr,none": 0.04236511258094632, "alias": "jurisprudence", "name": "mmlu_jurisprudence", "sample_len": 108 }, "mmlu_logical_fallacies": { "acc,none": 0.7116564417177914, "acc_stderr,none": 0.03559039531617345, "alias": "logical_fallacies", "name": "mmlu_logical_fallacies", "sample_len": 163 }, "mmlu_machine_learning": { "acc,none": 0.42857142857142855, "acc_stderr,none": 0.04697113923010208, "alias": "machine_learning", "name": "mmlu_machine_learning", "sample_len": 112 }, "mmlu_management": { "acc,none": 0.8543689320388349, "acc_stderr,none": 0.034926064766237934, "alias": "management", "name": "mmlu_management", "sample_len": 103 }, "mmlu_marketing": { "acc,none": 0.8461538461538461, "acc_stderr,none": 0.023636873317489267, "alias": "marketing", "name": "mmlu_marketing", "sample_len": 234 }, "mmlu_medical_genetics": { "acc,none": 0.73, "acc_stderr,none": 0.04461960433384737, "alias": "medical_genetics", "name": "mmlu_medical_genetics", "sample_len": 100 }, "mmlu_miscellaneous": { "acc,none": 0.8033205619412516, "acc_stderr,none": 0.014214138556913851, "alias": "miscellaneous", "name": "mmlu_miscellaneous", "sample_len": 783 }, "mmlu_moral_disputes": { "acc,none": 0.7138728323699421, "acc_stderr,none": 0.02433214677913417, "alias": "moral_disputes", "name": "mmlu_moral_disputes", "sample_len": 346 }, "mmlu_moral_scenarios": { "acc,none": 0.26927374301675977, "acc_stderr,none": 0.014835616582882544, "alias": "moral_scenarios", "name": "mmlu_moral_scenarios", "sample_len": 895 }, "mmlu_nutrition": { "acc,none": 0.7647058823529411, "acc_stderr,none": 0.02428861946604616, "alias": "nutrition", "name": "mmlu_nutrition", "sample_len": 306 }, "mmlu_other": { "acc,none": 0.6903765690376569, "acc_stderr,none": 0.00793504827765504, "alias": "other", "name": "mmlu_other", "sample_count": { "acc,none": 3107 }, "sample_len": 3107 }, "mmlu_philosophy": { "acc,none": 0.7041800643086816, "acc_stderr,none": 0.025922371788818833, "alias": "philosophy", "name": "mmlu_philosophy", "sample_len": 311 }, "mmlu_prehistory": { "acc,none": 0.7654320987654321, "acc_stderr,none": 0.0235768817440057, "alias": "prehistory", "name": "mmlu_prehistory", "sample_len": 324 }, "mmlu_professional_accounting": { "acc,none": 0.46808510638297873, "acc_stderr,none": 0.02976667507587383, "alias": "professional_accounting", "name": "mmlu_professional_accounting", "sample_len": 282 }, "mmlu_professional_law": { "acc,none": 0.4589308996088657, "acc_stderr,none": 0.0127270848267999, "alias": "professional_law", "name": "mmlu_professional_law", "sample_len": 1534 }, "mmlu_professional_medicine": { "acc,none": 0.5551470588235294, "acc_stderr,none": 0.030187532060329314, "alias": "professional_medicine", "name": "mmlu_professional_medicine", "sample_len": 272 }, "mmlu_professional_psychology": { "acc,none": 0.6993464052287581, "acc_stderr,none": 0.01855063450295291, "alias": "professional_psychology", "name": "mmlu_professional_psychology", "sample_len": 612 }, "mmlu_public_relations": { "acc,none": 0.6454545454545455, "acc_stderr,none": 0.04582004841505413, "alias": "public_relations", "name": "mmlu_public_relations", "sample_len": 110 }, "mmlu_security_studies": { "acc,none": 0.7428571428571429, "acc_stderr,none": 0.027979823538744557, "alias": "security_studies", "name": "mmlu_security_studies", "sample_len": 245 }, "mmlu_social_sciences": { "acc,none": 0.7565810854728632, "acc_stderr,none": 0.007580062219729006, "alias": "social sciences", "name": "mmlu_social_sciences", "sample_count": { "acc,none": 3077 }, "sample_len": 3077 }, "mmlu_sociology": { "acc,none": 0.835820895522388, "acc_stderr,none": 0.026193923544454094, "alias": "sociology", "name": "mmlu_sociology", "sample_len": 201 }, "mmlu_stem": { "acc,none": 0.5026958452267681, "acc_stderr,none": 0.008068176972734112, "alias": "stem", "name": "mmlu_stem", "sample_count": { "acc,none": 3153 }, "sample_len": 3153 }, "mmlu_us_foreign_policy": { "acc,none": 0.81, "acc_stderr,none": 0.039427724440366255, "alias": "us_foreign_policy", "name": "mmlu_us_foreign_policy", "sample_len": 100 }, "mmlu_virology": { "acc,none": 0.4759036144578313, "acc_stderr,none": 0.03887971849597268, "alias": "virology", "name": "mmlu_virology", "sample_len": 166 }, "mmlu_world_religions": { "acc,none": 0.8070175438596491, "acc_stderr,none": 0.030267457554898448, "alias": "world_religions", "name": "mmlu_world_religions", "sample_len": 171 } }, "system_instruction": null, "system_instruction_sha": null, "task_hashes": { "mmlu_abstract_algebra": "1ecc29cafeff483bf80347adc2878dae00d01596988032f438afce6291c8cfe7", "mmlu_anatomy": "51232e78f32967e0dd431bab9309f69be490f9998b4ddb93b641b09ba1f613cf", "mmlu_astronomy": "3e8d7c33bd0431518a3d5d4b1666bdabccf46c4cc4cfe95a3886cb2266743f86", "mmlu_business_ethics": "6ec93578c18c7bba58a384ecaa7e6e84c5e681262b34b1caa76abbbb0f9ebb02", "mmlu_clinical_knowledge": "cf39fec90aa76a379e440c1f0d5f5b04d9f32edc4004ffcfb8eadcc25c18b118", "mmlu_college_biology": "5378a297efa1cd71344228c95dcb29ba54757c7e527261400a4d65fd8ceed92b", "mmlu_college_chemistry": "714e60ea7e340f0344ffde41b247a19b68e6384152a1bdc9acc0ecf24cd0e7cd", "mmlu_college_computer_science": "2b66d244f98e61e6a78e5ed48b728e0ca2ca81c7757ccdd086fe6b0c1cf02da1", "mmlu_college_mathematics": "90b1ce25d7d38abd925181ae3aad095cfd783375fe8de0607a57420f47454f0f", "mmlu_college_medicine": "00cc41d26670913bdee6181e5b602726dde9f03e6a43236c2bf57486149845be", "mmlu_college_physics": "2abddb12a247904f9ba60b39766b19a8967c24fe8eee021022a353b93d73742c", "mmlu_computer_security": "8ffba21cebb9e39d5794c848a22e7e37cddff5c59f7b47a1d89872d9e8704b0c", "mmlu_conceptual_physics": "c0da3219fe7e5292dad2aa7e72790e3eba951711007cc57618b0850d941b85ec", "mmlu_econometrics": "bc667156b739500e02f7c8cb8f9621b6d62ea2011e1eaa3404cb45f6d16778ec", "mmlu_electrical_engineering": "0a02cb16a31ec7debba4190ab1cc31afadb9416764e0b074b9b96553f346b892", "mmlu_elementary_mathematics": "6048f1506468e757010d537a0ceedaadc587c18159a03e7664b5994843afedc2", "mmlu_formal_logic": "5fef452fe37d3c5aefce6276a26a839e5ee5d655d72adf50bbf0a8ae0e8d74e4", "mmlu_global_facts": "6163d6678b902c8cb5cd6c50f59bc0f31a9a356e977fcd6184614f48e3320e7a", "mmlu_high_school_biology": "2aabe83bb100a352d24a0136c24e612b68490bbe818c33f06cc6cee5379ecad8", "mmlu_high_school_chemistry": "dd3321fd42c8717094f57dd0eaeab0002d9ed192518a7de7aaef4913796c30f0", "mmlu_high_school_computer_science": "888aabb9a7ac77299e8b2b8429fa44c1fbbb5ac8165f556a0b00b347e51de3b5", "mmlu_high_school_european_history": "0b7be1963c7e224bffc18d72fe277408c4980f854a5fc94805fc008133640f44", "mmlu_high_school_geography": "915db5f9f9c584c6886ae92cfc28ad9c364bf685f22c15009ad8bf064b4a8027", "mmlu_high_school_government_and_politics": "411c6c6c179d1e2a252fab88f33123721540fc70f8223310e1f1349ec0b67753", "mmlu_high_school_macroeconomics": "291b29471838255d1a2dd704960610e98b7e3f2fd001e3aabc6b25be0c236e29", "mmlu_high_school_mathematics": "9b9567fc5c7875065ac91eac69621904f201cab822621440a2442a390f62b497", "mmlu_high_school_microeconomics": "6f4a887cb73beee5414248002f75216c16d7c8ff739b37a2607c6bcfad16712b", "mmlu_high_school_physics": "53edb93aefb6fc54fba283278bae10a58a7902902ff55edc30cb9c81745dbaa8", "mmlu_high_school_psychology": "ce01f01ff9a3bdc3e956ada7ec7c02f13771c386d076323056ac00eec0095785", "mmlu_high_school_statistics": "e0d652bf0cb6f927b0fc738e58a141f0ba8f9073615f4ddd70bf7a3b97998f21", "mmlu_high_school_us_history": "1b31fdc7e0d51803fa6107a0c7aa3b6968031bc449ed3513a7349956fa0b53d3", "mmlu_high_school_world_history": "9e352460adb245947aaf9671f135ae6484e44a115312955c45c7caaa0688f160", "mmlu_human_aging": "4b4276095e96dc6e2872517b2becc2ebe9fad0f42b321486f6f2ceaef81f385e", "mmlu_human_sexuality": "9395014a475c63632383587439df5c48c5dd3333eaa8d10ef9e0eaabd0997c3a", "mmlu_international_law": "3d2036ffe61014fa8a2de679c6bee2c0c3ade112f03cd55e4a6fba5bdc56bf7b", "mmlu_jurisprudence": "1548c06ef17823048b473d028f4889b3cf014beac4ac808521898ee141a34d23", "mmlu_logical_fallacies": "66f9691122f3fa813b86fda1131037c03cf42babe650c7374924f41882716332", "mmlu_machine_learning": "13ad1d3650a26d655a2a2eaa3be1f106d990e5b693b0e9006f8ebef221d2ed82", "mmlu_management": "84a18a4a3039f23b7dd18838c89a80171025a1a45eda3305464a3cfcd8257b69", "mmlu_marketing": "d6382d405e202221a78087356861723acb445fbd6f1db94152201f788b5c0606", "mmlu_medical_genetics": "b4546cc241c5811dddfec47d0bba37122fbd65545c93d60f50b993e810d37e2d", "mmlu_miscellaneous": "ecf4c3e0dc895ca5b7803d1b3f01fe3027b461f900ac001d36f5dd750c8eca1d", "mmlu_moral_disputes": "84f580166c00063790619588b4f9fcd2f800a6a04778f08c1bada043bfdc6ec0", "mmlu_moral_scenarios": "0dda4f43fd25e66311e64f4590698bfcc4c00c24ac58dbfec74b613512280ffc", "mmlu_nutrition": "732959f39ac0c6c0e9c3823082d3669467531cebfb5f7550d79bcc31e5cfdbce", "mmlu_philosophy": "ff6284cd5c6bfdb17898ef97dabc97916b70fc7485c57543edabdd44b1d8b543", "mmlu_prehistory": "efb58ea420f5b7975ff34766ddc7470676e1ababa0b4705bfdf150f6871fdd83", "mmlu_professional_accounting": "3c555bc35f86d097f509755f487781d2bd288de5dfe9aa59d8009a1dd0583c45", "mmlu_professional_law": "b108c04f61cbbb4b9351de3730d7e3396710c7702c6cf75703155dbfdbc7819d", "mmlu_professional_medicine": "0821fa48ca3715604bbef122215aea4e55f218dad6ba5191da2eb831971ac6f9", "mmlu_professional_psychology": "ab273adb58e2b365b3811e4ed4c6485c9630f78058580273703eb2573dde9010", "mmlu_public_relations": "da7dfa166f545d33a61c930908eee4f8d8544cad6328569b1c4b341becaf68f1", "mmlu_security_studies": "85ea8f6c3b791998f3c1d57164b6e28bcf4498f65fc1988dfa4a6a65d31fb505", "mmlu_sociology": "055d024e9587edc811c54e6cdd8fd74d535c6f5b1aad17cfd5f1598a1371606a", "mmlu_us_foreign_policy": "a99e6492b6831a5df8c7f4c76edf15b500e59ab4c87dc73fdbd61d43bc704682", "mmlu_virology": "ba4fc492ed4e9af97e30850257d2fdc5e7b53b37e7b4d68d443f7bd157aac21f", "mmlu_world_religions": "9634e441f5f53329b4b6c760b08b1a130f8f03b3cc1902b23d07f57db76b7263" }, "tokenizer_bos_token": [ null, "None" ], "tokenizer_eos_token": [ "<|im_end|>", "151645" ], "tokenizer_pad_token": [ "<|endoftext|>", "151643" ], "total_evaluation_time_seconds": "617.2125840899535", "transformers_version": "5.11.0", "upper_git_hash": null, "versions": { "mmlu": "2", "mmlu_abstract_algebra": 1.0, "mmlu_anatomy": 1.0, "mmlu_astronomy": 1.0, "mmlu_business_ethics": 1.0, "mmlu_clinical_knowledge": 1.0, "mmlu_college_biology": 1.0, "mmlu_college_chemistry": 1.0, "mmlu_college_computer_science": 1.0, "mmlu_college_mathematics": 1.0, "mmlu_college_medicine": 1.0, "mmlu_college_physics": 1.0, "mmlu_computer_security": 1.0, "mmlu_conceptual_physics": 1.0, "mmlu_econometrics": 1.0, "mmlu_electrical_engineering": 1.0, "mmlu_elementary_mathematics": 1.0, "mmlu_formal_logic": 1.0, "mmlu_global_facts": 1.0, "mmlu_high_school_biology": 1.0, "mmlu_high_school_chemistry": 1.0, "mmlu_high_school_computer_science": 1.0, "mmlu_high_school_european_history": 1.0, "mmlu_high_school_geography": 1.0, "mmlu_high_school_government_and_politics": 1.0, "mmlu_high_school_macroeconomics": 1.0, "mmlu_high_school_mathematics": 1.0, "mmlu_high_school_microeconomics": 1.0, "mmlu_high_school_physics": 1.0, "mmlu_high_school_psychology": 1.0, "mmlu_high_school_statistics": 1.0, "mmlu_high_school_us_history": 1.0, "mmlu_high_school_world_history": 1.0, "mmlu_human_aging": 1.0, "mmlu_human_sexuality": 1.0, "mmlu_humanities": "2", "mmlu_international_law": 1.0, "mmlu_jurisprudence": 1.0, "mmlu_logical_fallacies": 1.0, "mmlu_machine_learning": 1.0, "mmlu_management": 1.0, "mmlu_marketing": 1.0, "mmlu_medical_genetics": 1.0, "mmlu_miscellaneous": 1.0, "mmlu_moral_disputes": 1.0, "mmlu_moral_scenarios": 1.0, "mmlu_nutrition": 1.0, "mmlu_other": "2", "mmlu_philosophy": 1.0, "mmlu_prehistory": 1.0, "mmlu_professional_accounting": 1.0, "mmlu_professional_law": 1.0, "mmlu_professional_medicine": 1.0, "mmlu_professional_psychology": 1.0, "mmlu_public_relations": 1.0, "mmlu_security_studies": 1.0, "mmlu_social_sciences": "2", "mmlu_sociology": 1.0, "mmlu_stem": "2", "mmlu_us_foreign_policy": 1.0, "mmlu_virology": 1.0, "mmlu_world_religions": 1.0 } }