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{
  "results": {
    "ifeval": {
      "prompt_level_strict_acc,none": 0.45286506469500926,
      "prompt_level_strict_acc_stderr,none": 0.02142075394952955,
      "inst_level_strict_acc,none": 0.5515587529976019,
      "inst_level_strict_acc_stderr,none": "N/A",
      "prompt_level_loose_acc,none": 0.4879852125693161,
      "prompt_level_loose_acc_stderr,none": 0.02151036119343917,
      "inst_level_loose_acc,none": 0.5779376498800959,
      "inst_level_loose_acc_stderr,none": "N/A",
      "alias": "ifeval"
    }
  },
  "group_subtasks": {
    "ifeval": []
  },
  "configs": {
    "ifeval": {
      "task": "ifeval",
      "dataset_path": "wis-k/instruction-following-eval",
      "test_split": "train",
      "doc_to_text": "prompt",
      "doc_to_target": 0,
      "process_results": "def process_results(doc, results):\n    eval_logger.warning(\n        \"This task is meant for chat-finetuned models, and may not give meaningful results for models other than `openai` or `anthropic` if `doc_to_text` in its YAML is not wrapped in the appropriate chat template string. This warning will be removed when chat templating support is added natively to local models\"\n    )\n\n    inp = InputExample(\n        key=doc[\"key\"],\n        instruction_id_list=doc[\"instruction_id_list\"],\n        prompt=doc[\"prompt\"],\n        kwargs=doc[\"kwargs\"],\n    )\n    response = results[0]\n\n    out_strict = test_instruction_following_strict(inp, response)\n    out_loose = test_instruction_following_loose(inp, response)\n\n    return {\n        \"prompt_level_strict_acc\": out_strict.follow_all_instructions,\n        \"inst_level_strict_acc\": out_strict.follow_instruction_list,\n        \"prompt_level_loose_acc\": out_loose.follow_all_instructions,\n        \"inst_level_loose_acc\": out_loose.follow_instruction_list,\n    }\n",
      "description": "",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "num_fewshot": 0,
      "metric_list": [
        {
          "metric": "prompt_level_strict_acc",
          "aggregation": "mean",
          "higher_is_better": true
        },
        {
          "metric": "inst_level_strict_acc",
          "aggregation": "def agg_inst_level_acc(items):\n    flat_items = [item for sublist in items for item in sublist]\n    inst_level_acc = sum(flat_items) / len(flat_items)\n    return inst_level_acc\n",
          "higher_is_better": true
        },
        {
          "metric": "prompt_level_loose_acc",
          "aggregation": "mean",
          "higher_is_better": true
        },
        {
          "metric": "inst_level_loose_acc",
          "aggregation": "def agg_inst_level_acc(items):\n    flat_items = [item for sublist in items for item in sublist]\n    inst_level_acc = sum(flat_items) / len(flat_items)\n    return inst_level_acc\n",
          "higher_is_better": true
        }
      ],
      "output_type": "generate_until",
      "generation_kwargs": {
        "until": [],
        "do_sample": false,
        "temperature": 0.0,
        "max_gen_toks": 1280
      },
      "repeats": 1,
      "should_decontaminate": false,
      "metadata": {
        "version": 2.0
      }
    }
  },
  "versions": {
    "ifeval": 2.0
  },
  "n-shot": {
    "ifeval": 0
  },
  "higher_is_better": {
    "ifeval": {
      "prompt_level_strict_acc": true,
      "inst_level_strict_acc": true,
      "prompt_level_loose_acc": true,
      "inst_level_loose_acc": true
    }
  },
  "n-samples": {
    "ifeval": {
      "original": 541,
      "effective": 541
    }
  },
  "config": {
    "model": "local-chat-completions",
    "model_args": "base_url=http://localhost:7860/v1",
    "batch_size": 1,
    "batch_sizes": [],
    "device": null,
    "use_cache": null,
    "limit": null,
    "bootstrap_iters": 100000,
    "gen_kwargs": null,
    "random_seed": 0,
    "numpy_seed": 1234,
    "torch_seed": 1234,
    "fewshot_seed": 1234
  },
  "git_hash": "e39df01c",
  "date": 1717913696.062167,
  "pretty_env_info": "PyTorch version: 2.3.1+rocm6.0\nIs debug build: False\nCUDA used to build PyTorch: N/A\nROCM used to build PyTorch: 6.0.32830-d62f6a171\n\nOS: Arch Linux (x86_64)\nGCC version: (GCC) 14.1.1 20240522\nClang version: Could not collect\nCMake version: version 3.29.3\nLibc version: glibc-2.39\n\nPython version: 3.12.3 (main, Apr 23 2024, 09:16:07) [GCC 13.2.1 20240417] (64-bit runtime)\nPython platform: Linux-6.9.2-arch1-1-x86_64-with-glibc2.39\nIs CUDA available: True\nCUDA runtime version: Could not collect\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: AMD Radeon RX 7900 XTX (gfx1100)\nNvidia driver version: Could not collect\ncuDNN version: Could not collect\nHIP runtime version: 6.0.32830\nMIOpen runtime version: 3.0.0\nIs XNNPACK available: True\n\nCPU:\nArchitecture:                         x86_64\nCPU op-mode(s):                       32-bit, 64-bit\nAddress sizes:                        43 bits physical, 48 bits virtual\nByte Order:                           Little Endian\nCPU(s):                               16\nOn-line CPU(s) list:                  0-15\nVendor ID:                            AuthenticAMD\nModel name:                           AMD Ryzen 7 3700X 8-Core Processor\nCPU family:                           23\nModel:                                113\nThread(s) per core:                   2\nCore(s) per socket:                   8\nSocket(s):                            1\nStepping:                             0\nFrequency boost:                      enabled\nCPU(s) scaling MHz:                   82%\nCPU max MHz:                          4426.1709\nCPU min MHz:                          2200.0000\nBogoMIPS:                             7189.76\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 xtopology nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 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 hw_pstate ssbd mba ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sev sev_es\nVirtualization:                       AMD-V\nL1d cache:                            256 KiB (8 instances)\nL1i cache:                            256 KiB (8 instances)\nL2 cache:                             4 MiB (8 instances)\nL3 cache:                             32 MiB (2 instances)\nNUMA node(s):                         1\nNUMA node0 CPU(s):                    0-15\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 Reg file data sampling: Not affected\nVulnerability Retbleed:               Mitigation; untrained return thunk; SMT enabled with STIBP protection\nVulnerability Spec rstack overflow:   Mitigation; Safe RET\nVulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl\nVulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2:             Mitigation; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI 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==2.3.1+rocm6.0\n[pip3] torchaudio==2.3.1+rocm6.0\n[pip3] torchvision==0.18.1+rocm6.0\n[conda] Could not collect",
  "transformers_version": "4.41.2",
  "upper_git_hash": null,
  "task_hashes": {},
  "model_source": "local-chat-completions",
  "model_name": "",
  "model_name_sanitized": "",
  "system_instruction": null,
  "system_instruction_sha": null,
  "chat_template": null,
  "chat_template_sha": null,
  "start_time": 856951.670209348,
  "end_time": 859104.606258225,
  "total_evaluation_time_seconds": "2152.9360488770762"
}