SmolLM-1.7B-Instruct-quantized.w4a16
/
winogrande
/__nm__drive0__shashata__quantized_models__SmolLM-1.7B-Instruct-quantized.w4a16
/results_2024-08-22T01-20-08.883453.json
{ | |
"results": { | |
"winogrande": { | |
"alias": "winogrande", | |
"acc,none": 0.5887924230465666, | |
"acc_stderr,none": 0.013829128358676857 | |
} | |
}, | |
"group_subtasks": { | |
"winogrande": [] | |
}, | |
"configs": { | |
"winogrande": { | |
"task": "winogrande", | |
"dataset_path": "winogrande", | |
"dataset_name": "winogrande_xl", | |
"dataset_kwargs": { | |
"trust_remote_code": true | |
}, | |
"training_split": "train", | |
"validation_split": "validation", | |
"doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", | |
"doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", | |
"doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", | |
"description": "", | |
"target_delimiter": " ", | |
"fewshot_delimiter": "\n\n", | |
"num_fewshot": 5, | |
"metric_list": [ | |
{ | |
"metric": "acc", | |
"aggregation": "mean", | |
"higher_is_better": true | |
} | |
], | |
"output_type": "multiple_choice", | |
"repeats": 1, | |
"should_decontaminate": true, | |
"doc_to_decontamination_query": "sentence", | |
"metadata": { | |
"version": 1.0 | |
} | |
} | |
}, | |
"versions": { | |
"winogrande": 1.0 | |
}, | |
"n-shot": { | |
"winogrande": 5 | |
}, | |
"higher_is_better": { | |
"winogrande": { | |
"acc": true | |
} | |
}, | |
"n-samples": { | |
"winogrande": { | |
"original": 1267, | |
"effective": 1267 | |
} | |
}, | |
"config": { | |
"model": "sparseml", | |
"model_args": "pretrained=/nm/drive0/shashata/quantized_models/SmolLM-1.7B-Instruct-quantized.w4a16,dtype=bfloat16,max_legth=2048,add_bos_token=True,parallelize=True", | |
"model_num_parameters": 1761708032, | |
"model_dtype": "torch.bfloat16", | |
"model_revision": "main", | |
"model_sha": "", | |
"batch_size": "32", | |
"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": "4e55a1dd", | |
"date": 1724303835.3632848, | |
"pretty_env_info": "PyTorch version: 2.4.0+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.3 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.29.3\nLibc version: glibc-2.35\n\nPython version: 3.11.9 | packaged by conda-forge | (main, Apr 19 2024, 18:36:13) [GCC 12.3.0] (64-bit runtime)\nPython platform: Linux-5.15.0-91-generic-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.3.103\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: 545.23.08\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: 4900.20\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==1.26.4\n[pip3] onnx==1.14.1\n[pip3] onnxruntime==1.18.1\n[pip3] torch==2.4.0\n[pip3] triton==3.0.0\n[conda] Could not collect", | |
"transformers_version": "4.43.4", | |
"upper_git_hash": null, | |
"tokenizer_pad_token": [ | |
"<|im_end|>", | |
"2" | |
], | |
"tokenizer_eos_token": [ | |
"<|im_end|>", | |
"2" | |
], | |
"tokenizer_bos_token": [ | |
"<|im_start|>", | |
"1" | |
], | |
"eot_token_id": 2, | |
"max_length": 2048, | |
"task_hashes": {}, | |
"model_source": "sparseml", | |
"model_name": "/nm/drive0/shashata/quantized_models/SmolLM-1.7B-Instruct-quantized.w4a16", | |
"model_name_sanitized": "__nm__drive0__shashata__quantized_models__SmolLM-1.7B-Instruct-quantized.w4a16", | |
"system_instruction": null, | |
"system_instruction_sha": null, | |
"fewshot_as_multiturn": false, | |
"chat_template": null, | |
"chat_template_sha": null, | |
"start_time": 1874347.264972094, | |
"end_time": 1874525.978436142, | |
"total_evaluation_time_seconds": "178.7134640479926" | |
} |