Edit model card

Merge of top 7B models and the SLERP of other 7B models

mergekit is a toolkit for merging pre-trained language models. mergekit uses an out-of-core approach to perform unreasonably elaborate merges in resource-constrained situations. Merges can be run entirely on CPU or accelerated with as little as 8 GB of VRAM. Many merging algorithms are supported, with more coming as they catch my attention.

Eval

image/png

{
    "all": {
        "acc": 0.6568351479800627,
        "acc_stderr": 0.03199600851869088,
        "acc_norm": 0.6554901222242155,
        "acc_norm_stderr": 0.03267670432184765,
        "mc1": 0.5104039167686658,
        "mc1_stderr": 0.017499711430249268,
        "mc2": 0.6556430108444109,
        "mc2_stderr": 0.015519025079862213
    },
    "harness|arc:challenge|25": {
        "acc": 0.6919795221843004,
        "acc_stderr": 0.013491429517292038,
        "acc_norm": 0.7218430034129693,
        "acc_norm_stderr": 0.013094469919538812
    },
    "harness|hellaswag|10": {
        "acc": 0.7202748456482773,
        "acc_stderr": 0.0044794676194648,
        "acc_norm": 0.8828918542123083,
        "acc_norm_stderr": 0.003208919510309931
    },
    "harness|hendrycksTest-abstract_algebra|5": {
        "acc": 0.33,
        "acc_stderr": 0.047258156262526045,
        "acc_norm": 0.33,
        "acc_norm_stderr": 0.047258156262526045
    },
    "harness|hendrycksTest-anatomy|5": {
        "acc": 0.6518518518518519,
        "acc_stderr": 0.041153246103369526,
        "acc_norm": 0.6518518518518519,
        "acc_norm_stderr": 0.041153246103369526
    },
    "harness|hendrycksTest-astronomy|5": {
        "acc": 0.7039473684210527,
        "acc_stderr": 0.03715062154998904,
        "acc_norm": 0.7039473684210527,
        "acc_norm_stderr": 0.03715062154998904
    },
    "harness|hendrycksTest-business_ethics|5": {
        "acc": 0.66,
        "acc_stderr": 0.04760952285695238,
        "acc_norm": 0.66,
        "acc_norm_stderr": 0.04760952285695238
    },
    "harness|hendrycksTest-clinical_knowledge|5": {
        "acc": 0.6981132075471698,
        "acc_stderr": 0.02825420034443866,
        "acc_norm": 0.6981132075471698,
        "acc_norm_stderr": 0.02825420034443866
    },
    "harness|hendrycksTest-college_biology|5": {
        "acc": 0.7708333333333334,
        "acc_stderr": 0.03514697467862388,
        "acc_norm": 0.7708333333333334,
        "acc_norm_stderr": 0.03514697467862388
    },
    "harness|hendrycksTest-college_chemistry|5": {
        "acc": 0.48,
        "acc_stderr": 0.050211673156867795,
        "acc_norm": 0.48,
        "acc_norm_stderr": 0.050211673156867795
    },
    "harness|hendrycksTest-college_computer_science|5": {
        "acc": 0.52,
        "acc_stderr": 0.050211673156867795,
        "acc_norm": 0.52,
        "acc_norm_stderr": 0.050211673156867795
    },
    "harness|hendrycksTest-college_mathematics|5": {
        "acc": 0.27,
        "acc_stderr": 0.044619604333847394,
        "acc_norm": 0.27,
        "acc_norm_stderr": 0.044619604333847394
    },
    "harness|hendrycksTest-college_medicine|5": {
        "acc": 0.6705202312138728,
        "acc_stderr": 0.03583901754736412,
        "acc_norm": 0.6705202312138728,
        "acc_norm_stderr": 0.03583901754736412
    },
    "harness|hendrycksTest-college_physics|5": {
        "acc": 0.4019607843137255,
        "acc_stderr": 0.04878608714466996,
        "acc_norm": 0.4019607843137255,
        "acc_norm_stderr": 0.04878608714466996
    },
    "harness|hendrycksTest-computer_security|5": {
        "acc": 0.75,
        "acc_stderr": 0.04351941398892446,
        "acc_norm": 0.75,
        "acc_norm_stderr": 0.04351941398892446
    },
    "harness|hendrycksTest-conceptual_physics|5": {
        "acc": 0.5914893617021276,
        "acc_stderr": 0.032134180267015755,
        "acc_norm": 0.5914893617021276,
        "acc_norm_stderr": 0.032134180267015755
    },
    "harness|hendrycksTest-econometrics|5": {
        "acc": 0.5087719298245614,
        "acc_stderr": 0.04702880432049615,
        "acc_norm": 0.5087719298245614,
        "acc_norm_stderr": 0.04702880432049615
    },
    "harness|hendrycksTest-electrical_engineering|5": {
        "acc": 0.5724137931034483,
        "acc_stderr": 0.04122737111370332,
        "acc_norm": 0.5724137931034483,
        "acc_norm_stderr": 0.04122737111370332
    },
    "harness|hendrycksTest-elementary_mathematics|5": {
        "acc": 0.42592592592592593,
        "acc_stderr": 0.02546714904546955,
        "acc_norm": 0.42592592592592593,
        "acc_norm_stderr": 0.02546714904546955
    },
    "harness|hendrycksTest-formal_logic|5": {
        "acc": 0.49206349206349204,
        "acc_stderr": 0.044715725362943486,
        "acc_norm": 0.49206349206349204,
        "acc_norm_stderr": 0.044715725362943486
    },
    "harness|hendrycksTest-global_facts|5": {
        "acc": 0.37,
        "acc_stderr": 0.04852365870939099,
        "acc_norm": 0.37,
        "acc_norm_stderr": 0.04852365870939099
    },
    "harness|hendrycksTest-high_school_biology|5": {
        "acc": 0.7903225806451613,
        "acc_stderr": 0.023157879349083525,
        "acc_norm": 0.7903225806451613,
        "acc_norm_stderr": 0.023157879349083525
    },
    "harness|hendrycksTest-high_school_chemistry|5": {
        "acc": 0.5073891625615764,
        "acc_stderr": 0.035176035403610105,
        "acc_norm": 0.5073891625615764,
        "acc_norm_stderr": 0.035176035403610105
    },
    "harness|hendrycksTest-high_school_computer_science|5": {
        "acc": 0.66,
        "acc_stderr": 0.04760952285695237,
        "acc_norm": 0.66,
        "acc_norm_stderr": 0.04760952285695237
    },
    "harness|hendrycksTest-high_school_european_history|5": {
        "acc": 0.7757575757575758,
        "acc_stderr": 0.03256866661681102,
        "acc_norm": 0.7757575757575758,
        "acc_norm_stderr": 0.03256866661681102
    },
    "harness|hendrycksTest-high_school_geography|5": {
        "acc": 0.7929292929292929,
        "acc_stderr": 0.028869778460267045,
        "acc_norm": 0.7929292929292929,
        "acc_norm_stderr": 0.028869778460267045
    },
    "harness|hendrycksTest-high_school_government_and_politics|5": {
        "acc": 0.9067357512953368,
        "acc_stderr": 0.020986854593289733,
        "acc_norm": 0.9067357512953368,
        "acc_norm_stderr": 0.020986854593289733
    },
    "harness|hendrycksTest-high_school_macroeconomics|5": {
        "acc": 0.6666666666666666,
        "acc_stderr": 0.023901157979402534,
        "acc_norm": 0.6666666666666666,
        "acc_norm_stderr": 0.023901157979402534
    },
    "harness|hendrycksTest-high_school_mathematics|5": {
        "acc": 0.34814814814814815,
        "acc_stderr": 0.02904560029061625,
        "acc_norm": 0.34814814814814815,
        "acc_norm_stderr": 0.02904560029061625
    },
    "harness|hendrycksTest-high_school_microeconomics|5": {
        "acc": 0.6764705882352942,
        "acc_stderr": 0.030388353551886793,
        "acc_norm": 0.6764705882352942,
        "acc_norm_stderr": 0.030388353551886793
    },
    "harness|hendrycksTest-high_school_physics|5": {
        "acc": 0.36423841059602646,
        "acc_stderr": 0.03929111781242742,
        "acc_norm": 0.36423841059602646,
        "acc_norm_stderr": 0.03929111781242742
    },
    "harness|hendrycksTest-high_school_psychology|5": {
        "acc": 0.8366972477064221,
        "acc_stderr": 0.01584825580650155,
        "acc_norm": 0.8366972477064221,
        "acc_norm_stderr": 0.01584825580650155
    },
    "harness|hendrycksTest-high_school_statistics|5": {
        "acc": 0.5046296296296297,
        "acc_stderr": 0.03409825519163572,
        "acc_norm": 0.5046296296296297,
        "acc_norm_stderr": 0.03409825519163572
    },
    "harness|hendrycksTest-high_school_us_history|5": {
        "acc": 0.8529411764705882,
        "acc_stderr": 0.024857478080250447,
        "acc_norm": 0.8529411764705882,
        "acc_norm_stderr": 0.024857478080250447
    },
    "harness|hendrycksTest-high_school_world_history|5": {
        "acc": 0.8143459915611815,
        "acc_stderr": 0.025310495376944856,
        "acc_norm": 0.8143459915611815,
        "acc_norm_stderr": 0.025310495376944856
    },
    "harness|hendrycksTest-human_aging|5": {
        "acc": 0.6816143497757847,
        "acc_stderr": 0.03126580522513713,
        "acc_norm": 0.6816143497757847,
        "acc_norm_stderr": 0.03126580522513713
    },
    "harness|hendrycksTest-human_sexuality|5": {
        "acc": 0.7862595419847328,
        "acc_stderr": 0.0359546161177469,
        "acc_norm": 0.7862595419847328,
        "acc_norm_stderr": 0.0359546161177469
    },
    "harness|hendrycksTest-international_law|5": {
        "acc": 0.7933884297520661,
        "acc_stderr": 0.03695980128098824,
        "acc_norm": 0.7933884297520661,
        "acc_norm_stderr": 0.03695980128098824
    },
    "harness|hendrycksTest-jurisprudence|5": {
        "acc": 0.7870370370370371,
        "acc_stderr": 0.0395783547198098,
        "acc_norm": 0.7870370370370371,
        "acc_norm_stderr": 0.0395783547198098
    },
    "harness|hendrycksTest-logical_fallacies|5": {
        "acc": 0.7730061349693251,
        "acc_stderr": 0.03291099578615769,
        "acc_norm": 0.7730061349693251,
        "acc_norm_stderr": 0.03291099578615769
    },
    "harness|hendrycksTest-machine_learning|5": {
        "acc": 0.48214285714285715,
        "acc_stderr": 0.047427623612430116,
        "acc_norm": 0.48214285714285715,
        "acc_norm_stderr": 0.047427623612430116
    },
    "harness|hendrycksTest-management|5": {
        "acc": 0.7864077669902912,
        "acc_stderr": 0.040580420156460344,
        "acc_norm": 0.7864077669902912,
        "acc_norm_stderr": 0.040580420156460344
    },
    "harness|hendrycksTest-marketing|5": {
        "acc": 0.8803418803418803,
        "acc_stderr": 0.021262719400406974,
        "acc_norm": 0.8803418803418803,
        "acc_norm_stderr": 0.021262719400406974
    },
    "harness|hendrycksTest-medical_genetics|5": {
        "acc": 0.73,
        "acc_stderr": 0.0446196043338474,
        "acc_norm": 0.73,
        "acc_norm_stderr": 0.0446196043338474
    },
    "harness|hendrycksTest-miscellaneous|5": {
        "acc": 0.8275862068965517,
        "acc_stderr": 0.013507943909371802,
        "acc_norm": 0.8275862068965517,
        "acc_norm_stderr": 0.013507943909371802
    },
    "harness|hendrycksTest-moral_disputes|5": {
        "acc": 0.7543352601156069,
        "acc_stderr": 0.023176298203992005,
        "acc_norm": 0.7543352601156069,
        "acc_norm_stderr": 0.023176298203992005
    },
    "harness|hendrycksTest-moral_scenarios|5": {
        "acc": 0.45027932960893857,
        "acc_stderr": 0.01663961523684581,
        "acc_norm": 0.45027932960893857,
        "acc_norm_stderr": 0.01663961523684581
    },
    "harness|hendrycksTest-nutrition|5": {
        "acc": 0.7254901960784313,
        "acc_stderr": 0.02555316999182652,
        "acc_norm": 0.7254901960784313,
        "acc_norm_stderr": 0.02555316999182652
    },
    "harness|hendrycksTest-philosophy|5": {
        "acc": 0.7138263665594855,
        "acc_stderr": 0.025670259242188933,
        "acc_norm": 0.7138263665594855,
        "acc_norm_stderr": 0.025670259242188933
    },
    "harness|hendrycksTest-prehistory|5": {
        "acc": 0.7561728395061729,
        "acc_stderr": 0.02389187954195961,
        "acc_norm": 0.7561728395061729,
        "acc_norm_stderr": 0.02389187954195961
    },
    "harness|hendrycksTest-professional_accounting|5": {
        "acc": 0.46808510638297873,
        "acc_stderr": 0.029766675075873866,
        "acc_norm": 0.46808510638297873,
        "acc_norm_stderr": 0.029766675075873866
    },
    "harness|hendrycksTest-professional_law|5": {
        "acc": 0.4745762711864407,
        "acc_stderr": 0.012753716929101004,
        "acc_norm": 0.4745762711864407,
        "acc_norm_stderr": 0.012753716929101004
    },
    "harness|hendrycksTest-professional_medicine|5": {
        "acc": 0.6911764705882353,
        "acc_stderr": 0.02806499816704009,
        "acc_norm": 0.6911764705882353,
        "acc_norm_stderr": 0.02806499816704009
    },
    "harness|hendrycksTest-professional_psychology|5": {
        "acc": 0.6748366013071896,
        "acc_stderr": 0.01895088677080631,
        "acc_norm": 0.6748366013071896,
        "acc_norm_stderr": 0.01895088677080631
    },
    "harness|hendrycksTest-public_relations|5": {
        "acc": 0.6545454545454545,
        "acc_stderr": 0.04554619617541054,
        "acc_norm": 0.6545454545454545,
        "acc_norm_stderr": 0.04554619617541054
    },
    "harness|hendrycksTest-security_studies|5": {
        "acc": 0.7346938775510204,
        "acc_stderr": 0.028263889943784603,
        "acc_norm": 0.7346938775510204,
        "acc_norm_stderr": 0.028263889943784603
    },
    "harness|hendrycksTest-sociology|5": {
        "acc": 0.8258706467661692,
        "acc_stderr": 0.026814951200421603,
        "acc_norm": 0.8258706467661692,
        "acc_norm_stderr": 0.026814951200421603
    },
    "harness|hendrycksTest-us_foreign_policy|5": {
        "acc": 0.85,
        "acc_stderr": 0.03588702812826371,
        "acc_norm": 0.85,
        "acc_norm_stderr": 0.03588702812826371
    },
    "harness|hendrycksTest-virology|5": {
        "acc": 0.5602409638554217,
        "acc_stderr": 0.03864139923699122,
        "acc_norm": 0.5602409638554217,
        "acc_norm_stderr": 0.03864139923699122
    },
    "harness|hendrycksTest-world_religions|5": {
        "acc": 0.8421052631578947,
        "acc_stderr": 0.027966785859160893,
        "acc_norm": 0.8421052631578947,
        "acc_norm_stderr": 0.027966785859160893
    },
    "harness|truthfulqa:mc|0": {
        "mc1": 0.5104039167686658,
        "mc1_stderr": 0.017499711430249268,
        "mc2": 0.6556430108444109,
        "mc2_stderr": 0.015519025079862213
    },
    "harness|winogrande|5": {
        "acc": 0.8516179952644041,
        "acc_stderr": 0.009990706005184136
    },
    "harness|gsm8k|5": {
        "acc": 0.7338893100833965,
        "acc_stderr": 0.012172750939040328
    }
}

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 74.94
AI2 Reasoning Challenge (25-Shot) 72.18
HellaSwag (10-Shot) 88.29
MMLU (5-Shot) 65.03
TruthfulQA (0-shot) 65.56
Winogrande (5-shot) 85.16
GSM8k (5-shot) 73.39
Downloads last month
79
Safetensors
Model size
7.24B params
Tensor type
BF16
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for MaziyarPanahi/TheTop-5x7B-Instruct-S4-v0.1

Quantizations
1 model

Collection including MaziyarPanahi/TheTop-5x7B-Instruct-S4-v0.1

Evaluation results