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kbl emnlp24 evaluation results

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@@ -56,3 +56,50 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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bar-exam/w_rag/bar-exam-rag-p/gpt-4o-2024-05-13/results_2024-06-08T03-56-10.438787.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": {
+      "exact_match,get-answer": 0.425,
+      "exact_match_stderr,get-answer": 0.07915823166939517
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": {
+      "task": "kbl_bar_exam_em_criminal_2024_q_rag_bm25",
+      "group": [
+        "kbl_bar_exam_em_criminal_q_rag_bm25"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/criminal/rag_v2_bm25_q_rag/criminal2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_bm25(doc):\n    context = build_context_q(doc, n_max_context=2)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": {
+      "original": 40,
+      "effective": 40
+    }
+  },
+  "config": {
+    "model": "openai-chat-completions",
+    "model_args": "model=gpt-4o-2024-05-13,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "910eb31c",
+  "date": 1717833309.983085,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.36.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": "f0c1c52f2937177e2ca2a869d45b30420c0394d03fce72a42c8a11874d5e1643"
+  },
+  "model_source": "openai-chat-completions",
+  "model_name": "gpt-4o-2024-05-13",
+  "model_name_sanitized": "gpt-4o-2024-05-13",
+  "start_time": 6578919.357919418,
+  "end_time": 6578988.531092423,
+  "total_evaluation_time_seconds": "69.17317300476134"
+}

bar-exam/w_rag/bar-exam-rag-p/gpt-4o-2024-05-13/results_2024-06-08T04-01-23.919136.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": {
+      "exact_match,get-answer": 0.5428571428571428,
+      "exact_match_stderr,get-answer": 0.05997140203803456
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": {
+      "task": "kbl_bar_exam_em_civil_2024_q_rag_bm25",
+      "group": [
+        "kbl_bar_exam_em_civil_q_rag_bm25"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/civil/rag_v2_bm25_q_rag/civil2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_bm25(doc):\n    context = build_context_q(doc, n_max_context=2)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": {
+      "original": 70,
+      "effective": 70
+    }
+  },
+  "config": {
+    "model": "openai-chat-completions",
+    "model_args": "model=gpt-4o-2024-05-13,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "910eb31c",
+  "date": 1717833604.0699265,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.36.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": "9f52c509b1426b64b8e7e8a3be4056850357b092102a62f6a017f68f5ee1bd9b"
+  },
+  "model_source": "openai-chat-completions",
+  "model_name": "gpt-4o-2024-05-13",
+  "model_name_sanitized": "gpt-4o-2024-05-13",
+  "start_time": 6579215.510191211,
+  "end_time": 6579302.011842481,
+  "total_evaluation_time_seconds": "86.50165127031505"
+}

bar-exam/w_rag/bar-exam-rag-p/gpt-4o-2024-05-13/results_2024-06-08T04-03-41.153201.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": {
+      "exact_match,get-answer": 0.5571428571428572,
+      "exact_match_stderr,get-answer": 0.05979853784717617
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": {
+      "task": "kbl_bar_exam_em_civil_2024_q_rag_bm25",
+      "group": [
+        "kbl_bar_exam_em_civil_q_rag_bm25"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/civil/rag_v2_bm25_q_rag/civil2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_bm25(doc):\n    context = build_context_q(doc, n_max_context=2)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": {
+      "original": 70,
+      "effective": 70
+    }
+  },
+  "config": {
+    "model": "openai-chat-completions",
+    "model_args": "model=gpt-4o-2024-05-13,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "910eb31c",
+  "date": 1717833745.052095,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.36.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": "9f52c509b1426b64b8e7e8a3be4056850357b092102a62f6a017f68f5ee1bd9b"
+  },
+  "model_source": "openai-chat-completions",
+  "model_name": "gpt-4o-2024-05-13",
+  "model_name_sanitized": "gpt-4o-2024-05-13",
+  "start_time": 6579356.149858083,
+  "end_time": 6579439.246138226,
+  "total_evaluation_time_seconds": "83.09628014359623"
+}

bar-exam/w_rag/bar-exam-rag-p/gpt-4o-2024-05-13/results_2024-06-08T04-06-01.443913.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": {
+      "exact_match,get-answer": 0.5571428571428572,
+      "exact_match_stderr,get-answer": 0.05979853784717617
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": {
+      "task": "kbl_bar_exam_em_civil_2024_q_rag_bm25",
+      "group": [
+        "kbl_bar_exam_em_civil_q_rag_bm25"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/civil/rag_v2_bm25_q_rag/civil2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_bm25(doc):\n    context = build_context_q(doc, n_max_context=2)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": {
+      "original": 70,
+      "effective": 70
+    }
+  },
+  "config": {
+    "model": "openai-chat-completions",
+    "model_args": "model=gpt-4o-2024-05-13,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "910eb31c",
+  "date": 1717833881.7548149,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.36.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25": "9f52c509b1426b64b8e7e8a3be4056850357b092102a62f6a017f68f5ee1bd9b"
+  },
+  "model_source": "openai-chat-completions",
+  "model_name": "gpt-4o-2024-05-13",
+  "model_name_sanitized": "gpt-4o-2024-05-13",
+  "start_time": 6579493.195687779,
+  "end_time": 6579579.536854439,
+  "total_evaluation_time_seconds": "86.34116666018963"
+}

bar-exam/w_rag/bar-exam-rag-p/gpt-4o-2024-05-13/results_2024-06-08T04-08-32.829412.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": {
+      "exact_match,get-answer": 0.425,
+      "exact_match_stderr,get-answer": 0.07915823166939517
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": {
+      "task": "kbl_bar_exam_em_criminal_2024_q_rag_bm25",
+      "group": [
+        "kbl_bar_exam_em_criminal_q_rag_bm25"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/criminal/rag_v2_bm25_q_rag/criminal2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_bm25(doc):\n    context = build_context_q(doc, n_max_context=2)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": {
+      "original": 40,
+      "effective": 40
+    }
+  },
+  "config": {
+    "model": "openai-chat-completions",
+    "model_args": "model=gpt-4o-2024-05-13,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "910eb31c",
+  "date": 1717834053.2753696,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.36.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": "f0c1c52f2937177e2ca2a869d45b30420c0394d03fce72a42c8a11874d5e1643"
+  },
+  "model_source": "openai-chat-completions",
+  "model_name": "gpt-4o-2024-05-13",
+  "model_name_sanitized": "gpt-4o-2024-05-13",
+  "start_time": 6579664.738595345,
+  "end_time": 6579730.922176821,
+  "total_evaluation_time_seconds": "66.18358147609979"
+}

bar-exam/w_rag/bar-exam-rag-p/gpt-4o-2024-05-13/results_2024-06-08T04-09-58.765972.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": {
+      "exact_match,get-answer": 0.4,
+      "exact_match_stderr,get-answer": 0.07844645405527362
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": {
+      "task": "kbl_bar_exam_em_criminal_2024_q_rag_bm25",
+      "group": [
+        "kbl_bar_exam_em_criminal_q_rag_bm25"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/criminal/rag_v2_bm25_q_rag/criminal2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_bm25(doc):\n    context = build_context_q(doc, n_max_context=2)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": {
+      "original": 40,
+      "effective": 40
+    }
+  },
+  "config": {
+    "model": "openai-chat-completions",
+    "model_args": "model=gpt-4o-2024-05-13,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "910eb31c",
+  "date": 1717834142.1671739,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.36.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25": "f0c1c52f2937177e2ca2a869d45b30420c0394d03fce72a42c8a11874d5e1643"
+  },
+  "model_source": "openai-chat-completions",
+  "model_name": "gpt-4o-2024-05-13",
+  "model_name_sanitized": "gpt-4o-2024-05-13",
+  "start_time": 6579753.557459239,
+  "end_time": 6579816.858468568,
+  "total_evaluation_time_seconds": "63.30100932903588"
+}

bar-exam/w_rag/bar-exam-rag-p/gpt-4o-2024-05-13/results_2024-06-08T04-13-31.578888.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": {
+      "exact_match,get-answer": 0.55,
+      "exact_match_stderr,get-answer": 0.07966275068156915
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": {
+      "task": "kbl_bar_exam_em_public_2024_q_rag_bm25",
+      "group": [
+        "kbl_bar_exam_em_public_q_rag_bm25"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/public/rag_v2_bm25_q_rag/public2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_bm25(doc):\n    context = build_context_q(doc, n_max_context=2)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": {
+      "original": 40,
+      "effective": 40
+    }
+  },
+  "config": {
+    "model": "openai-chat-completions",
+    "model_args": "model=gpt-4o-2024-05-13,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "910eb31c",
+  "date": 1717834346.2819638,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.36.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": "10e5016ac6b48018f1a2387b66a19485a16c54044e1af4604ad92c676c159840"
+  },
+  "model_source": "openai-chat-completions",
+  "model_name": "gpt-4o-2024-05-13",
+  "model_name_sanitized": "gpt-4o-2024-05-13",
+  "start_time": 6579957.744287782,
+  "end_time": 6580029.67087784,
+  "total_evaluation_time_seconds": "71.92659005802125"
+}

bar-exam/w_rag/bar-exam-rag-p/gpt-4o-2024-05-13/results_2024-06-08T04-15-06.499056.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": {
+      "exact_match,get-answer": 0.55,
+      "exact_match_stderr,get-answer": 0.07966275068156915
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": {
+      "task": "kbl_bar_exam_em_public_2024_q_rag_bm25",
+      "group": [
+        "kbl_bar_exam_em_public_q_rag_bm25"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/public/rag_v2_bm25_q_rag/public2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_bm25(doc):\n    context = build_context_q(doc, n_max_context=2)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": {
+      "original": 40,
+      "effective": 40
+    }
+  },
+  "config": {
+    "model": "openai-chat-completions",
+    "model_args": "model=gpt-4o-2024-05-13,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "910eb31c",
+  "date": 1717834441.03897,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.36.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": "10e5016ac6b48018f1a2387b66a19485a16c54044e1af4604ad92c676c159840"
+  },
+  "model_source": "openai-chat-completions",
+  "model_name": "gpt-4o-2024-05-13",
+  "model_name_sanitized": "gpt-4o-2024-05-13",
+  "start_time": 6580052.39003367,
+  "end_time": 6580124.590481056,
+  "total_evaluation_time_seconds": "72.20044738613069"
+}

bar-exam/w_rag/bar-exam-rag-p/gpt-4o-2024-05-13/results_2024-06-08T04-16-26.392355.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": {
+      "exact_match,get-answer": 0.575,
+      "exact_match_stderr,get-answer": 0.07915823166939517
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": {
+      "task": "kbl_bar_exam_em_public_2024_q_rag_bm25",
+      "group": [
+        "kbl_bar_exam_em_public_q_rag_bm25"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/public/rag_v2_bm25_q_rag/public2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_bm25(doc):\n    context = build_context_q(doc, n_max_context=2)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": {
+      "original": 40,
+      "effective": 40
+    }
+  },
+  "config": {
+    "model": "openai-chat-completions",
+    "model_args": "model=gpt-4o-2024-05-13,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "910eb31c",
+  "date": 1717834532.6042576,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.36.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25": "10e5016ac6b48018f1a2387b66a19485a16c54044e1af4604ad92c676c159840"
+  },
+  "model_source": "openai-chat-completions",
+  "model_name": "gpt-4o-2024-05-13",
+  "model_name_sanitized": "gpt-4o-2024-05-13",
+  "start_time": 6580144.105884912,
+  "end_time": 6580204.484642479,
+  "total_evaluation_time_seconds": "60.37875756621361"
+}

bar-exam/w_rag/bar-exam-rag-p/gpt-4o-2024-05-13/samples_kbl_bar_exam_em_criminal_2023_qa2_rag_bm25_2024-06-08T03-41-03.067990.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:56868ee7edf1a59116fe961d9181bb0c17c292e4a269eb571e5151c2f685ce00
+size 36303816

bar-exam/w_rag/bar-exam-rag-ps/claude-3-opus-20240229/results_2024-06-16T23-10-21.713801.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": {
+      "exact_match,get-answer": 0.325,
+      "exact_match_stderr,get-answer": 0.07499999999999998
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": {
+      "task": "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute",
+      "group": [
+        "kbl_bar_exam_em_criminal_q_rag_bm25_precedent_and_statute"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/criminal/rag_v2_bm25_q_rag_precedent_statue/criminal2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_n3(doc):\n    context = build_context_q(doc, n_max_context=3)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": {
+      "original": 40,
+      "effective": 40
+    }
+  },
+  "config": {
+    "model": "anthropic-chat-completions",
+    "model_args": "model=claude-3-opus-20240229,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "db6019ad",
+  "date": 1718593347.068955,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.41.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": "f4cb3887e81e12b389095b02ee35b02ccf52a0c8ecc93d75c045d31b0722e7b7"
+  },
+  "model_source": "anthropic-chat-completions",
+  "model_name": "claude-3-opus-20240229",
+  "model_name_sanitized": "claude-3-opus-20240229",
+  "start_time": 7338960.422549035,
+  "end_time": 7339439.806635085,
+  "total_evaluation_time_seconds": "479.38408604916185"
+}

bar-exam/w_rag/bar-exam-rag-ps/claude-3-opus-20240229/results_2024-06-16T23-12-27.582676.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": {
+      "exact_match,get-answer": 0.425,
+      "exact_match_stderr,get-answer": 0.07915823166939516
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": {
+      "task": "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute",
+      "group": [
+        "kbl_bar_exam_em_public_q_rag_bm25_precedent_and_statute"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/public/rag_v2_bm25_q_rag_precedent_statute/public2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_n4(doc):\n    context = build_context_q(doc, n_max_context=4)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": {
+      "original": 40,
+      "effective": 40
+    }
+  },
+  "config": {
+    "model": "anthropic-chat-completions",
+    "model_args": "model=claude-3-opus-20240229,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "db6019ad",
+  "date": 1718593371.3297691,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.41.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": "29e2575d7d7a816fb69311835f067bb06777b2af347caf934931b79cd247f2bd"
+  },
+  "model_source": "anthropic-chat-completions",
+  "model_name": "claude-3-opus-20240229",
+  "model_name_sanitized": "claude-3-opus-20240229",
+  "start_time": 7338984.711161967,
+  "end_time": 7339565.674845466,
+  "total_evaluation_time_seconds": "580.9636834990233"
+}

bar-exam/w_rag/bar-exam-rag-ps/claude-3-opus-20240229/results_2024-06-16T23-14-45.428795.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": {
+      "exact_match,get-answer": 0.21428571428571427,
+      "exact_match_stderr,get-answer": 0.04939743391486606
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": {
+      "task": "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute",
+      "group": [
+        "kbl_bar_exam_em_civil_q_rag_bm25_precedent_and_statute"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/civil/rag_v2_bm25_q_rag_precedent_statute/civil2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_n3(doc):\n    context = build_context_q(doc, n_max_context=3)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": {
+      "original": 70,
+      "effective": 70
+    }
+  },
+  "config": {
+    "model": "anthropic-chat-completions",
+    "model_args": "model=claude-3-opus-20240229,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
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+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "db6019ad",
+  "date": 1718593363.9269989,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.41.2",
+  "upper_git_hash": null,
+  "task_hashes": {
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+  },
+  "model_source": "anthropic-chat-completions",
+  "model_name": "claude-3-opus-20240229",
+  "model_name_sanitized": "claude-3-opus-20240229",
+  "start_time": 7338977.24180854,
+  "end_time": 7339703.521488148,
+  "total_evaluation_time_seconds": "726.2796796076"
+}

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bar-exam/w_rag/bar-exam-rag-ps/claude-3-sonnet-20240229/results_2024-06-16T23-10-29.281534.json

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+{
+  "results": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": {
+      "exact_match,get-answer": 0.125,
+      "exact_match_stderr,get-answer": 0.05295740910852021
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": {
+      "task": "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute",
+      "group": [
+        "kbl_bar_exam_em_criminal_q_rag_bm25_precedent_and_statute"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/criminal/rag_v2_bm25_q_rag_precedent_statue/criminal2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_n3(doc):\n    context = build_context_q(doc, n_max_context=3)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": {
+      "original": 40,
+      "effective": 40
+    }
+  },
+  "config": {
+    "model": "anthropic-chat-completions",
+    "model_args": "model=claude-3-sonnet-20240229,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "db6019ad",
+  "date": 1718593224.2729626,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.41.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": "f4cb3887e81e12b389095b02ee35b02ccf52a0c8ecc93d75c045d31b0722e7b7"
+  },
+  "model_source": "anthropic-chat-completions",
+  "model_name": "claude-3-sonnet-20240229",
+  "model_name_sanitized": "claude-3-sonnet-20240229",
+  "start_time": 7338837.559190894,
+  "end_time": 7339447.37377631,
+  "total_evaluation_time_seconds": "609.8145854165778"
+}

bar-exam/w_rag/bar-exam-rag-ps/claude-3-sonnet-20240229/results_2024-06-16T23-14-51.845284.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": {
+      "exact_match,get-answer": 0.21428571428571427,
+      "exact_match_stderr,get-answer": 0.04939743391486606
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": {
+      "task": "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute",
+      "group": [
+        "kbl_bar_exam_em_civil_q_rag_bm25_precedent_and_statute"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/civil/rag_v2_bm25_q_rag_precedent_statute/civil2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_n3(doc):\n    context = build_context_q(doc, n_max_context=3)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": {
+      "original": 70,
+      "effective": 70
+    }
+  },
+  "config": {
+    "model": "anthropic-chat-completions",
+    "model_args": "model=claude-3-sonnet-20240229,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "db6019ad",
+  "date": 1718593205.0155938,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.41.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": "868a22d8d7e4a5564ae19f2c51d778197856dbfa3479fc9f689b1a8baa306d5c"
+  },
+  "model_source": "anthropic-chat-completions",
+  "model_name": "claude-3-sonnet-20240229",
+  "model_name_sanitized": "claude-3-sonnet-20240229",
+  "start_time": 7338818.311583444,
+  "end_time": 7339709.937982192,
+  "total_evaluation_time_seconds": "891.6263987487182"
+}

bar-exam/w_rag/bar-exam-rag-ps/claude-3-sonnet-20240229/results_2024-06-16T23-14-59.153309.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": {
+      "exact_match,get-answer": 0.225,
+      "exact_match_stderr,get-answer": 0.06686668711812967
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": {
+      "task": "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute",
+      "group": [
+        "kbl_bar_exam_em_public_q_rag_bm25_precedent_and_statute"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/public/rag_v2_bm25_q_rag_precedent_statute/public2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_n4(doc):\n    context = build_context_q(doc, n_max_context=4)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": {
+      "original": 40,
+      "effective": 40
+    }
+  },
+  "config": {
+    "model": "anthropic-chat-completions",
+    "model_args": "model=claude-3-sonnet-20240229,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "db6019ad",
+  "date": 1718593325.8677251,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.41.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": "29e2575d7d7a816fb69311835f067bb06777b2af347caf934931b79cd247f2bd"
+  },
+  "model_source": "anthropic-chat-completions",
+  "model_name": "claude-3-sonnet-20240229",
+  "model_name_sanitized": "claude-3-sonnet-20240229",
+  "start_time": 7338939.226972311,
+  "end_time": 7339717.245722948,
+  "total_evaluation_time_seconds": "778.0187506368384"
+}

bar-exam/w_rag/bar-exam-rag-ps/claude-3-sonnet-20240229/samples_kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute_2024-06-16T23-14-51.845284.json

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bar-exam/w_rag/bar-exam-rag-ps/claude-3-sonnet-20240229/samples_kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute_2024-06-16T23-10-29.281534.json

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bar-exam/w_rag/bar-exam-rag-ps/claude-3.5-sonnet-20240620/results_2024-06-20T21-24-38.364883.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_criminal_2024_q_rag": {
+      "exact_match,get-answer": 0.5,
+      "exact_match_stderr,get-answer": 0.08006407690254357
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_criminal_2024_q_rag": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_criminal_2024_q_rag": {
+      "task": "kbl_bar_exam_em_criminal_2024_q_rag",
+      "group": [
+        "kbl_bar_exam_em_criminal_q_rag"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/criminal/rag/criminal2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag(doc):\n    context = build_context_q(doc, n_max_context=3)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_criminal_2024_q_rag": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_criminal_2024_q_rag": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_criminal_2024_q_rag": {
+      "original": 40,
+      "effective": 40
+    }
+  },
+  "config": {
+    "model": "anthropic-chat-completions",
+    "model_args": "model=claude-3-5-sonnet-20240620,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "67b64f22",
+  "date": 1718932793.05654,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.41.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_criminal_2024_q_rag": "d18c72daf59fe01994a771ab248880709c3b8a587e671f90a3ea9c726ef68350"
+  },
+  "model_source": "anthropic-chat-completions",
+  "model_name": "claude-3-5-sonnet-20240620",
+  "model_name_sanitized": "claude-3-5-sonnet-20240620",
+  "start_time": 7678405.855609578,
+  "end_time": 7678696.45714848,
+  "total_evaluation_time_seconds": "290.6015389021486"
+}

bar-exam/w_rag/bar-exam-rag-ps/claude-3.5-sonnet-20240620/results_2024-06-20T21-25-09.293289.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_public_2024_q_rag": {
+      "exact_match,get-answer": 0.5,
+      "exact_match_stderr,get-answer": 0.08006407690254357
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_public_2024_q_rag": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_public_2024_q_rag": {
+      "task": "kbl_bar_exam_em_public_2024_q_rag",
+      "group": [
+        "kbl_bar_exam_em_public_q_rag"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/public/rag/public2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag(doc):\n    context = build_context_q(doc, n_max_context=3)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_public_2024_q_rag": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_public_2024_q_rag": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_public_2024_q_rag": {
+      "original": 40,
+      "effective": 40
+    }
+  },
+  "config": {
+    "model": "anthropic-chat-completions",
+    "model_args": "model=claude-3-5-sonnet-20240620,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "67b64f22",
+  "date": 1718932826.4780552,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.41.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_public_2024_q_rag": "f9ab9f6dc961f6101acd478b52d9238705ad3ae1511b08cc6f6047d05fcfedf9"
+  },
+  "model_source": "anthropic-chat-completions",
+  "model_name": "claude-3-5-sonnet-20240620",
+  "model_name_sanitized": "claude-3-5-sonnet-20240620",
+  "start_time": 7678439.299011347,
+  "end_time": 7678727.386164072,
+  "total_evaluation_time_seconds": "288.0871527250856"
+}

bar-exam/w_rag/bar-exam-rag-ps/claude-3.5-sonnet-20240620/results_2024-06-20T21-28-31.755241.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_civil_2024_q_rag": {
+      "exact_match,get-answer": 0.38571428571428573,
+      "exact_match_stderr,get-answer": 0.058599447926148025
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_civil_2024_q_rag": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_civil_2024_q_rag": {
+      "task": "kbl_bar_exam_em_civil_2024_q_rag",
+      "group": [
+        "kbl_bar_exam_em_civil_q_rag"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/civil/rag/civil2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag(doc):\n    context = build_context_q(doc, n_max_context=3)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_civil_2024_q_rag": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_civil_2024_q_rag": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_civil_2024_q_rag": {
+      "original": 70,
+      "effective": 70
+    }
+  },
+  "config": {
+    "model": "anthropic-chat-completions",
+    "model_args": "model=claude-3-5-sonnet-20240620,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "67b64f22",
+  "date": 1718932803.2535107,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.41.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_civil_2024_q_rag": "b113f714b5cdeb6f31fd89fb214dc9df97ffdc46cfccc6491895d022a427c959"
+  },
+  "model_source": "anthropic-chat-completions",
+  "model_name": "claude-3-5-sonnet-20240620",
+  "model_name_sanitized": "claude-3-5-sonnet-20240620",
+  "start_time": 7678416.150427681,
+  "end_time": 7678929.84792572,
+  "total_evaluation_time_seconds": "513.6974980384111"
+}

bar-exam/w_rag/bar-exam-rag-ps/gpt-4o-2024-05-13/results_2024-06-09T03-48-56.209580.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": {
+      "exact_match,get-answer": 0.525,
+      "exact_match_stderr,get-answer": 0.07996393417804536
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": {
+      "task": "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute",
+      "group": [
+        "kbl_bar_exam_em_public_q_rag_bm25_precedent_and_statute"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/public/rag_v2_bm25_q_rag_precedent_statute/public2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_n4(doc):\n    context = build_context_q(doc, n_max_context=4)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": {
+      "original": 40,
+      "effective": 40
+    }
+  },
+  "config": {
+    "model": "openai-chat-completions",
+    "model_args": "model=gpt-4o-2024-05-13,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "37dec914",
+  "date": 1717919258.9767256,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.36.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": "29e2575d7d7a816fb69311835f067bb06777b2af347caf934931b79cd247f2bd"
+  },
+  "model_source": "openai-chat-completions",
+  "model_name": "gpt-4o-2024-05-13",
+  "model_name_sanitized": "gpt-4o-2024-05-13",
+  "start_time": 6664872.352388805,
+  "end_time": 6664954.301303226,
+  "total_evaluation_time_seconds": "81.94891442079097"
+}

bar-exam/w_rag/bar-exam-rag-ps/gpt-4o-2024-05-13/results_2024-06-09T03-50-11.634293.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": {
+      "exact_match,get-answer": 0.525,
+      "exact_match_stderr,get-answer": 0.07996393417804536
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": {
+      "task": "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute",
+      "group": [
+        "kbl_bar_exam_em_public_q_rag_bm25_precedent_and_statute"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/public/rag_v2_bm25_q_rag_precedent_statute/public2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_n4(doc):\n    context = build_context_q(doc, n_max_context=4)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": {
+      "original": 40,
+      "effective": 40
+    }
+  },
+  "config": {
+    "model": "openai-chat-completions",
+    "model_args": "model=gpt-4o-2024-05-13,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "37dec914",
+  "date": 1717919338.6750934,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.36.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_public_2024_q_rag_bm25_precedent_and_statute": "29e2575d7d7a816fb69311835f067bb06777b2af347caf934931b79cd247f2bd"
+  },
+  "model_source": "openai-chat-completions",
+  "model_name": "gpt-4o-2024-05-13",
+  "model_name_sanitized": "gpt-4o-2024-05-13",
+  "start_time": 6664952.052684998,
+  "end_time": 6665029.726791014,
+  "total_evaluation_time_seconds": "77.67410601582378"
+}

bar-exam/w_rag/bar-exam-rag-ps/gpt-4o-2024-05-13/results_2024-06-09T03-58-24.530449.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": {
+      "exact_match,get-answer": 0.45,
+      "exact_match_stderr,get-answer": 0.07966275068156915
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": {
+      "task": "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute",
+      "group": [
+        "kbl_bar_exam_em_criminal_q_rag_bm25_precedent_and_statute"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/criminal/rag_v2_bm25_q_rag_precedent_statue/criminal2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_n3(doc):\n    context = build_context_q(doc, n_max_context=3)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": {
+      "original": 40,
+      "effective": 40
+    }
+  },
+  "config": {
+    "model": "openai-chat-completions",
+    "model_args": "model=gpt-4o-2024-05-13,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "37dec914",
+  "date": 1717919846.7842455,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.36.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": "f4cb3887e81e12b389095b02ee35b02ccf52a0c8ecc93d75c045d31b0722e7b7"
+  },
+  "model_source": "openai-chat-completions",
+  "model_name": "gpt-4o-2024-05-13",
+  "model_name_sanitized": "gpt-4o-2024-05-13",
+  "start_time": 6665460.201428375,
+  "end_time": 6665522.623242918,
+  "total_evaluation_time_seconds": "62.42181454319507"
+}

bar-exam/w_rag/bar-exam-rag-ps/gpt-4o-2024-05-13/results_2024-06-09T04-00-52.567793.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": {
+      "exact_match,get-answer": 0.5,
+      "exact_match_stderr,get-answer": 0.08006407690254357
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": {
+      "task": "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute",
+      "group": [
+        "kbl_bar_exam_em_criminal_q_rag_bm25_precedent_and_statute"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/criminal/rag_v2_bm25_q_rag_precedent_statue/criminal2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_n3(doc):\n    context = build_context_q(doc, n_max_context=3)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": {
+      "original": 40,
+      "effective": 40
+    }
+  },
+  "config": {
+    "model": "openai-chat-completions",
+    "model_args": "model=gpt-4o-2024-05-13,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "37dec914",
+  "date": 1717919997.555986,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.36.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": "f4cb3887e81e12b389095b02ee35b02ccf52a0c8ecc93d75c045d31b0722e7b7"
+  },
+  "model_source": "openai-chat-completions",
+  "model_name": "gpt-4o-2024-05-13",
+  "model_name_sanitized": "gpt-4o-2024-05-13",
+  "start_time": 6665610.942040785,
+  "end_time": 6665670.660366702,
+  "total_evaluation_time_seconds": "59.71832591667771"
+}

bar-exam/w_rag/bar-exam-rag-ps/gpt-4o-2024-05-13/results_2024-06-09T04-02-58.888824.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": {
+      "exact_match,get-answer": 0.45,
+      "exact_match_stderr,get-answer": 0.07966275068156915
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": {
+      "task": "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute",
+      "group": [
+        "kbl_bar_exam_em_criminal_q_rag_bm25_precedent_and_statute"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/criminal/rag_v2_bm25_q_rag_precedent_statue/criminal2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_n3(doc):\n    context = build_context_q(doc, n_max_context=3)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": {
+      "original": 40,
+      "effective": 40
+    }
+  },
+  "config": {
+    "model": "openai-chat-completions",
+    "model_args": "model=gpt-4o-2024-05-13,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "37dec914",
+  "date": 1717920121.4991667,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.36.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_criminal_2024_q_rag_bm25_precedent_and_statute": "f4cb3887e81e12b389095b02ee35b02ccf52a0c8ecc93d75c045d31b0722e7b7"
+  },
+  "model_source": "openai-chat-completions",
+  "model_name": "gpt-4o-2024-05-13",
+  "model_name_sanitized": "gpt-4o-2024-05-13",
+  "start_time": 6665734.827410657,
+  "end_time": 6665796.981502802,
+  "total_evaluation_time_seconds": "62.15409214515239"
+}

bar-exam/w_rag/bar-exam-rag-ps/gpt-4o-2024-05-13/results_2024-06-09T04-19-13.458074.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": {
+      "exact_match,get-answer": 0.5,
+      "exact_match_stderr,get-answer": 0.0601929265428846
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": {
+      "task": "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute",
+      "group": [
+        "kbl_bar_exam_em_civil_q_rag_bm25_precedent_and_statute"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/civil/rag_v2_bm25_q_rag_precedent_statute/civil2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_n3(doc):\n    context = build_context_q(doc, n_max_context=3)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": {
+      "original": 70,
+      "effective": 70
+    }
+  },
+  "config": {
+    "model": "openai-chat-completions",
+    "model_args": "model=gpt-4o-2024-05-13,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "37dec914",
+  "date": 1717921058.9995453,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.36.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": "868a22d8d7e4a5564ae19f2c51d778197856dbfa3479fc9f689b1a8baa306d5c"
+  },
+  "model_source": "openai-chat-completions",
+  "model_name": "gpt-4o-2024-05-13",
+  "model_name_sanitized": "gpt-4o-2024-05-13",
+  "start_time": 6666672.465024059,
+  "end_time": 6666771.550486732,
+  "total_evaluation_time_seconds": "99.08546267356724"
+}

bar-exam/w_rag/bar-exam-rag-ps/gpt-4o-2024-05-13/results_2024-06-09T04-21-01.117340.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": {
+      "exact_match,get-answer": 0.5285714285714286,
+      "exact_match_stderr,get-answer": 0.06009457202204595
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": {
+      "task": "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute",
+      "group": [
+        "kbl_bar_exam_em_civil_q_rag_bm25_precedent_and_statute"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/civil/rag_v2_bm25_q_rag_precedent_statute/civil2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_n3(doc):\n    context = build_context_q(doc, n_max_context=3)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": {
+      "original": 70,
+      "effective": 70
+    }
+  },
+  "config": {
+    "model": "openai-chat-completions",
+    "model_args": "model=gpt-4o-2024-05-13,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "37dec914",
+  "date": 1717921171.5562367,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.36.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": "868a22d8d7e4a5564ae19f2c51d778197856dbfa3479fc9f689b1a8baa306d5c"
+  },
+  "model_source": "openai-chat-completions",
+  "model_name": "gpt-4o-2024-05-13",
+  "model_name_sanitized": "gpt-4o-2024-05-13",
+  "start_time": 6666784.951349439,
+  "end_time": 6666879.209665118,
+  "total_evaluation_time_seconds": "94.2583156786859"
+}

bar-exam/w_rag/bar-exam-rag-ps/gpt-4o-2024-05-13/results_2024-06-09T04-22-47.887081.json

@@ -0,0 +1,106 @@
+{
+  "results": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": {
+      "exact_match,get-answer": 0.4714285714285714,
+      "exact_match_stderr,get-answer": 0.06009457202204595
+    }
+  },
+  "group_subtasks": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": []
+  },
+  "configs": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": {
+      "task": "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute",
+      "group": [
+        "kbl_bar_exam_em_civil_q_rag_bm25_precedent_and_statute"
+      ],
+      "dataset_path": "json",
+      "dataset_name": "kbl_bar_exam",
+      "dataset_kwargs": {
+        "data_files": {
+          "test": "raw_data/kbl_20240525/bar_exam/civil/rag_v2_bm25_q_rag_precedent_statute/civil2024.rag.json"
+        }
+      },
+      "test_split": "test",
+      "doc_to_text": "def doc_to_text_q_rag_n3(doc):\n    context = build_context_q(doc, n_max_context=3)\n    return build_tempate(doc, context)\n",
+      "doc_to_target": "gt",
+      "description": "당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "num_fewshot": 0,
+      "metric_list": [
+        {
+          "metric": "exact_match",
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": true
+        }
+      ],
+      "output_type": "generate_until",
+      "generation_kwargs": {
+        "until": [
+          "\n\n"
+        ],
+        "do_sample": false
+      },
+      "repeats": 1,
+      "filter_list": [
+        {
+          "name": "get-answer",
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "([A-E]).*"
+            },
+            {
+              "function": "take_first"
+            }
+          ]
+        }
+      ],
+      "should_decontaminate": false
+    }
+  },
+  "versions": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": "Yaml"
+  },
+  "n-shot": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": 0
+  },
+  "n-samples": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": {
+      "original": 70,
+      "effective": 70
+    }
+  },
+  "config": {
+    "model": "openai-chat-completions",
+    "model_args": "model=gpt-4o-2024-05-13,temperature=0",
+    "batch_size": 1,
+    "batch_sizes": [],
+    "device": null,
+    "use_cache": null,
+    "limit": 2000.0,
+    "bootstrap_iters": 100000,
+    "gen_kwargs": {},
+    "random_seed": 0,
+    "numpy_seed": 1234,
+    "torch_seed": 1234,
+    "fewshot_seed": 1234
+  },
+  "git_hash": "37dec914",
+  "date": 1717921275.0896323,
+  "pretty_env_info": "PyTorch version: 2.1.2+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.22.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                       x86_64\nCPU op-mode(s):                     32-bit, 64-bit\nAddress sizes:                      48 bits physical, 48 bits virtual\nByte Order:                         Little Endian\nCPU(s):                             256\nOn-line CPU(s) list:                0-255\nVendor ID:                          AuthenticAMD\nModel name:                         AMD EPYC 7763 64-Core Processor\nCPU family:                         25\nModel:                              1\nThread(s) per core:                 2\nCore(s) per socket:                 64\nSocket(s):                          2\nStepping:                           1\nFrequency boost:                    enabled\nCPU max MHz:                        3529.0520\nCPU min MHz:                        1500.0000\nBogoMIPS:                           4899.84\nFlags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm\nVirtualization:                     AMD-V\nL1d cache:                          4 MiB (128 instances)\nL1i cache:                          4 MiB (128 instances)\nL2 cache:                           64 MiB (128 instances)\nL3 cache:                           512 MiB (16 instances)\nNUMA node(s):                       2\nNUMA node0 CPU(s):                  0-63,128-191\nNUMA node1 CPU(s):                  64-127,192-255\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit:        Not affected\nVulnerability L1tf:                 Not affected\nVulnerability Mds:                  Not affected\nVulnerability Meltdown:             Not affected\nVulnerability Mmio stale data:      Not affected\nVulnerability Retbleed:             Not affected\nVulnerability Spec rstack overflow: Mitigation; safe RET\nVulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds:                Not affected\nVulnerability Tsx async abort:      Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.3\n[pip3] torch==2.1.2\n[pip3] triton==2.1.0\n[conda] Could not collect",
+  "transformers_version": "4.36.2",
+  "upper_git_hash": null,
+  "task_hashes": {
+    "kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute": "868a22d8d7e4a5564ae19f2c51d778197856dbfa3479fc9f689b1a8baa306d5c"
+  },
+  "model_source": "openai-chat-completions",
+  "model_name": "gpt-4o-2024-05-13",
+  "model_name_sanitized": "gpt-4o-2024-05-13",
+  "start_time": 6666888.466171417,
+  "end_time": 6666985.979539955,
+  "total_evaluation_time_seconds": "97.51336853764951"
+}

bar-exam/w_rag/bar-exam-rag-ps/gpt-4o-2024-05-13/samples_kbl_bar_exam_em_civil_2024_q_rag_bm25_precedent_and_statute_2024-06-09T04-19-13.458074.json

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