pankajmathur
/

orca_mini_v6_8b

@@ -1,193 +0,0 @@
-{
-  "results": {
-    "leaderboard_musr": {
-      " ": " ",
-      "alias": "leaderboard_musr"
-    },
-    "leaderboard_musr_murder_mysteries": {
-      "alias": " - leaderboard_musr_murder_mysteries",
-      "acc_norm,none": 0.536,
-      "acc_norm_stderr,none": 0.03160397514522374
-    },
-    "leaderboard_musr_object_placements": {
-      "alias": " - leaderboard_musr_object_placements",
-      "acc_norm,none": 0.375,
-      "acc_norm_stderr,none": 0.03031695312954162
-    },
-    "leaderboard_musr_team_allocation": {
-      "alias": " - leaderboard_musr_team_allocation",
-      "acc_norm,none": 0.316,
-      "acc_norm_stderr,none": 0.029462657598578676
-    }
-  },
-  "group_subtasks": {
-    "leaderboard_musr": [
-      "leaderboard_musr_murder_mysteries",
-      "leaderboard_musr_object_placements",
-      "leaderboard_musr_team_allocation"
-    ]
-  },
-  "configs": {
-    "leaderboard_musr_murder_mysteries": {
-      "task": "leaderboard_musr_murder_mysteries",
-      "dataset_path": "TAUR-Lab/MuSR",
-      "test_split": "murder_mysteries",
-      "doc_to_text": "def doc_to_text(doc):\n    \"\"\"\n    Convert a doc to text.\n    \"\"\"\n    choices = \"\"\n    for i, choice in enumerate(ast.literal_eval(doc[\"choices\"])):\n        choices += f\"{i+1} - {choice}\\n\"\n\n    text = DOC_TO_TEXT.format(\n        narrative=doc[\"narrative\"], question=doc[\"question\"], choices=choices\n    )\n\n    return text\n",
-      "doc_to_target": "{{answer_choice}}",
-      "doc_to_choice": "{{choices}}",
-      "description": "",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "num_fewshot": 0,
-      "metric_list": [
-        {
-          "metric": "acc_norm",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.0
-      }
-    },
-    "leaderboard_musr_object_placements": {
-      "task": "leaderboard_musr_object_placements",
-      "dataset_path": "TAUR-Lab/MuSR",
-      "test_split": "object_placements",
-      "doc_to_text": "def doc_to_text(doc):\n    \"\"\"\n    Convert a doc to text.\n    \"\"\"\n    choices = \"\"\n    for i, choice in enumerate(ast.literal_eval(doc[\"choices\"])):\n        choices += f\"{i+1} - {choice}\\n\"\n\n    text = DOC_TO_TEXT.format(\n        narrative=doc[\"narrative\"], question=doc[\"question\"], choices=choices\n    )\n\n    return text\n",
-      "doc_to_target": "{{answer_choice}}",
-      "doc_to_choice": "{{choices}}",
-      "description": "",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "num_fewshot": 0,
-      "metric_list": [
-        {
-          "metric": "acc_norm",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.0
-      }
-    },
-    "leaderboard_musr_team_allocation": {
-      "task": "leaderboard_musr_team_allocation",
-      "dataset_path": "TAUR-Lab/MuSR",
-      "test_split": "team_allocation",
-      "doc_to_text": "def doc_to_text(doc):\n    \"\"\"\n    Convert a doc to text.\n    \"\"\"\n    choices = \"\"\n    for i, choice in enumerate(ast.literal_eval(doc[\"choices\"])):\n        choices += f\"{i+1} - {choice}\\n\"\n\n    text = DOC_TO_TEXT.format(\n        narrative=doc[\"narrative\"], question=doc[\"question\"], choices=choices\n    )\n\n    return text\n",
-      "doc_to_target": "{{answer_choice}}",
-      "doc_to_choice": "{{choices}}",
-      "description": "",
-      "target_delimiter": " ",
-      "fewshot_delimiter": "\n\n",
-      "num_fewshot": 0,
-      "metric_list": [
-        {
-          "metric": "acc_norm",
-          "aggregation": "mean",
-          "higher_is_better": true
-        }
-      ],
-      "output_type": "multiple_choice",
-      "repeats": 1,
-      "should_decontaminate": false,
-      "metadata": {
-        "version": 1.0
-      }
-    }
-  },
-  "versions": {
-    "leaderboard_musr_murder_mysteries": 1.0,
-    "leaderboard_musr_object_placements": 1.0,
-    "leaderboard_musr_team_allocation": 1.0
-  },
-  "n-shot": {
-    "leaderboard_musr_murder_mysteries": 0,
-    "leaderboard_musr_object_placements": 0,
-    "leaderboard_musr_team_allocation": 0
-  },
-  "higher_is_better": {
-    "leaderboard_musr": {
-      "acc_norm": true
-    },
-    "leaderboard_musr_murder_mysteries": {
-      "acc_norm": true
-    },
-    "leaderboard_musr_object_placements": {
-      "acc_norm": true
-    },
-    "leaderboard_musr_team_allocation": {
-      "acc_norm": true
-    }
-  },
-  "n-samples": {
-    "leaderboard_musr_murder_mysteries": {
-      "original": 250,
-      "effective": 250
-    },
-    "leaderboard_musr_object_placements": {
-      "original": 256,
-      "effective": 256
-    },
-    "leaderboard_musr_team_allocation": {
-      "original": 250,
-      "effective": 250
-    }
-  },
-  "config": {
-    "model": "hf",
-    "model_args": "pretrained=pankajmathur/orca_mini_v6_8b,dtype=bfloat16",
-    "batch_size": "auto",
-    "batch_sizes": [
-      16
-    ],
-    "device": "cuda:0",
-    "use_cache": "cache_pankajmathur/orca_mini_v6_8b/leaderboard_musr",
-    "limit": null,
-    "bootstrap_iters": 100000,
-    "gen_kwargs": null,
-    "random_seed": 0,
-    "numpy_seed": 1234,
-    "torch_seed": 1234,
-    "fewshot_seed": 1234
-  },
-  "git_hash": "773209c",
-  "date": 1720544771.2678711,
-  "pretty_env_info": "PyTorch version: 2.2.0+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: Could not collect\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-5.15.0-60-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.1.105\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: GPU 0: NVIDIA A100-SXM4-80GB\nNvidia driver version: 535.104.05\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:                        4900.18\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 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\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):                    8\nNUMA node0 CPU(s):               0-15,128-143\nNUMA node1 CPU(s):               16-31,144-159\nNUMA node2 CPU(s):               32-47,160-175\nNUMA node3 CPU(s):               48-63,176-191\nNUMA node4 CPU(s):               64-79,192-207\nNUMA node5 CPU(s):               80-95,208-223\nNUMA node6 CPU(s):               96-111,224-239\nNUMA node7 CPU(s):               112-127,240-255\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 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==2.2.0\n[pip3] torchaudio==2.2.0\n[pip3] torchvision==0.17.0\n[pip3] triton==2.2.0\n[conda] Could not collect",
-  "transformers_version": "4.42.3",
-  "upper_git_hash": "be01651cf6b611c09f088c336db74ea625227716",
-  "tokenizer_pad_token": [
-    "<|end_of_text|>",
-    "128001"
-  ],
-  "tokenizer_eos_token": [
-    "<|im_end|>",
-    "128256"
-  ],
-  "tokenizer_bos_token": [
-    "<|begin_of_text|>",
-    "128000"
-  ],
-  "eot_token_id": 128256,
-  "max_length": 8192,
-  "task_hashes": {},
-  "model_source": "hf",
-  "model_name": "pankajmathur/orca_mini_v6_8b",
-  "model_name_sanitized": "pankajmathur__orca_mini_v6_8b",
-  "system_instruction": null,
-  "system_instruction_sha": null,
-  "fewshot_as_multiturn": false,
-  "chat_template": null,
-  "chat_template_sha": null,
-  "start_time": 25392059.053773217,
-  "end_time": 25392794.03587531,
-  "total_evaluation_time_seconds": "734.9821020923555"
-}