{
  "best_metric": 0.8391241431236267,
  "best_model_checkpoint": "./output_v2/7b_cluster031_Nous-Hermes-llama-2-7b_partitioned_v3_standardized_031/checkpoint-800",
  "epoch": 0.5503955968352253,
  "global_step": 800,
  "is_hyper_param_search": false,
  "is_local_process_zero": true,
  "is_world_process_zero": true,
  "log_history": [
    {
      "epoch": 0.01,
      "learning_rate": 0.0002,
      "loss": 0.9502,
      "step": 10
    },
    {
      "epoch": 0.01,
      "learning_rate": 0.0002,
      "loss": 0.9426,
      "step": 20
    },
    {
      "epoch": 0.02,
      "learning_rate": 0.0002,
      "loss": 0.9682,
      "step": 30
    },
    {
      "epoch": 0.03,
      "learning_rate": 0.0002,
      "loss": 0.8517,
      "step": 40
    },
    {
      "epoch": 0.03,
      "learning_rate": 0.0002,
      "loss": 0.8944,
      "step": 50
    },
    {
      "epoch": 0.04,
      "learning_rate": 0.0002,
      "loss": 0.8608,
      "step": 60
    },
    {
      "epoch": 0.05,
      "learning_rate": 0.0002,
      "loss": 0.915,
      "step": 70
    },
    {
      "epoch": 0.06,
      "learning_rate": 0.0002,
      "loss": 0.8349,
      "step": 80
    },
    {
      "epoch": 0.06,
      "learning_rate": 0.0002,
      "loss": 0.8912,
      "step": 90
    },
    {
      "epoch": 0.07,
      "learning_rate": 0.0002,
      "loss": 0.876,
      "step": 100
    },
    {
      "epoch": 0.08,
      "learning_rate": 0.0002,
      "loss": 0.8697,
      "step": 110
    },
    {
      "epoch": 0.08,
      "learning_rate": 0.0002,
      "loss": 0.8604,
      "step": 120
    },
    {
      "epoch": 0.09,
      "learning_rate": 0.0002,
      "loss": 0.8654,
      "step": 130
    },
    {
      "epoch": 0.1,
      "learning_rate": 0.0002,
      "loss": 0.8804,
      "step": 140
    },
    {
      "epoch": 0.1,
      "learning_rate": 0.0002,
      "loss": 0.8355,
      "step": 150
    },
    {
      "epoch": 0.11,
      "learning_rate": 0.0002,
      "loss": 0.8704,
      "step": 160
    },
    {
      "epoch": 0.12,
      "learning_rate": 0.0002,
      "loss": 0.8241,
      "step": 170
    },
    {
      "epoch": 0.12,
      "learning_rate": 0.0002,
      "loss": 0.8523,
      "step": 180
    },
    {
      "epoch": 0.13,
      "learning_rate": 0.0002,
      "loss": 0.845,
      "step": 190
    },
    {
      "epoch": 0.14,
      "learning_rate": 0.0002,
      "loss": 0.8681,
      "step": 200
    },
    {
      "epoch": 0.14,
      "eval_loss": 0.8539559245109558,
      "eval_runtime": 189.7934,
      "eval_samples_per_second": 5.269,
      "eval_steps_per_second": 2.634,
      "step": 200
    },
    {
      "epoch": 0.14,
      "mmlu_eval_accuracy": 0.47295530665862845,
      "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
      "mmlu_eval_accuracy_anatomy": 0.5,
      "mmlu_eval_accuracy_astronomy": 0.375,
      "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
      "mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655,
      "mmlu_eval_accuracy_college_biology": 0.4375,
      "mmlu_eval_accuracy_college_chemistry": 0.125,
      "mmlu_eval_accuracy_college_computer_science": 0.45454545454545453,
      "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
      "mmlu_eval_accuracy_college_medicine": 0.36363636363636365,
      "mmlu_eval_accuracy_college_physics": 0.45454545454545453,
      "mmlu_eval_accuracy_computer_security": 0.45454545454545453,
      "mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
      "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
      "mmlu_eval_accuracy_electrical_engineering": 0.5,
      "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
      "mmlu_eval_accuracy_formal_logic": 0.35714285714285715,
      "mmlu_eval_accuracy_global_facts": 0.5,
      "mmlu_eval_accuracy_high_school_biology": 0.34375,
      "mmlu_eval_accuracy_high_school_chemistry": 0.36363636363636365,
      "mmlu_eval_accuracy_high_school_computer_science": 0.7777777777777778,
      "mmlu_eval_accuracy_high_school_european_history": 0.7222222222222222,
      "mmlu_eval_accuracy_high_school_geography": 0.7272727272727273,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.3023255813953488,
      "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.34615384615384615,
      "mmlu_eval_accuracy_high_school_physics": 0.35294117647058826,
      "mmlu_eval_accuracy_high_school_psychology": 0.7166666666666667,
      "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
      "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
      "mmlu_eval_accuracy_high_school_world_history": 0.5769230769230769,
      "mmlu_eval_accuracy_human_aging": 0.6956521739130435,
      "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
      "mmlu_eval_accuracy_international_law": 0.6923076923076923,
      "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
      "mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
      "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
      "mmlu_eval_accuracy_management": 0.7272727272727273,
      "mmlu_eval_accuracy_marketing": 0.76,
      "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
      "mmlu_eval_accuracy_miscellaneous": 0.6744186046511628,
      "mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
      "mmlu_eval_accuracy_moral_scenarios": 0.24,
      "mmlu_eval_accuracy_nutrition": 0.5757575757575758,
      "mmlu_eval_accuracy_philosophy": 0.4117647058823529,
      "mmlu_eval_accuracy_prehistory": 0.42857142857142855,
      "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
      "mmlu_eval_accuracy_professional_law": 0.32941176470588235,
      "mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
      "mmlu_eval_accuracy_professional_psychology": 0.391304347826087,
      "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
      "mmlu_eval_accuracy_security_studies": 0.5185185185185185,
      "mmlu_eval_accuracy_sociology": 0.6818181818181818,
      "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
      "mmlu_eval_accuracy_virology": 0.4444444444444444,
      "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
      "mmlu_loss": 1.2187759077891358,
      "step": 200
    },
    {
      "epoch": 0.14,
      "learning_rate": 0.0002,
      "loss": 0.8902,
      "step": 210
    },
    {
      "epoch": 0.15,
      "learning_rate": 0.0002,
      "loss": 0.9119,
      "step": 220
    },
    {
      "epoch": 0.16,
      "learning_rate": 0.0002,
      "loss": 0.8849,
      "step": 230
    },
    {
      "epoch": 0.17,
      "learning_rate": 0.0002,
      "loss": 0.8345,
      "step": 240
    },
    {
      "epoch": 0.17,
      "learning_rate": 0.0002,
      "loss": 0.8418,
      "step": 250
    },
    {
      "epoch": 0.18,
      "learning_rate": 0.0002,
      "loss": 0.8305,
      "step": 260
    },
    {
      "epoch": 0.19,
      "learning_rate": 0.0002,
      "loss": 0.8525,
      "step": 270
    },
    {
      "epoch": 0.19,
      "learning_rate": 0.0002,
      "loss": 0.8523,
      "step": 280
    },
    {
      "epoch": 0.2,
      "learning_rate": 0.0002,
      "loss": 0.8511,
      "step": 290
    },
    {
      "epoch": 0.21,
      "learning_rate": 0.0002,
      "loss": 0.8297,
      "step": 300
    },
    {
      "epoch": 0.21,
      "learning_rate": 0.0002,
      "loss": 0.8213,
      "step": 310
    },
    {
      "epoch": 0.22,
      "learning_rate": 0.0002,
      "loss": 0.8225,
      "step": 320
    },
    {
      "epoch": 0.23,
      "learning_rate": 0.0002,
      "loss": 0.8359,
      "step": 330
    },
    {
      "epoch": 0.23,
      "learning_rate": 0.0002,
      "loss": 0.8326,
      "step": 340
    },
    {
      "epoch": 0.24,
      "learning_rate": 0.0002,
      "loss": 0.832,
      "step": 350
    },
    {
      "epoch": 0.25,
      "learning_rate": 0.0002,
      "loss": 0.8208,
      "step": 360
    },
    {
      "epoch": 0.25,
      "learning_rate": 0.0002,
      "loss": 0.8427,
      "step": 370
    },
    {
      "epoch": 0.26,
      "learning_rate": 0.0002,
      "loss": 0.8812,
      "step": 380
    },
    {
      "epoch": 0.27,
      "learning_rate": 0.0002,
      "loss": 0.9016,
      "step": 390
    },
    {
      "epoch": 0.28,
      "learning_rate": 0.0002,
      "loss": 0.8694,
      "step": 400
    },
    {
      "epoch": 0.28,
      "eval_loss": 0.8468822240829468,
      "eval_runtime": 189.8705,
      "eval_samples_per_second": 5.267,
      "eval_steps_per_second": 2.633,
      "step": 400
    },
    {
      "epoch": 0.28,
      "mmlu_eval_accuracy": 0.45864815481629223,
      "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
      "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
      "mmlu_eval_accuracy_astronomy": 0.375,
      "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
      "mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655,
      "mmlu_eval_accuracy_college_biology": 0.4375,
      "mmlu_eval_accuracy_college_chemistry": 0.125,
      "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
      "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
      "mmlu_eval_accuracy_college_medicine": 0.3181818181818182,
      "mmlu_eval_accuracy_college_physics": 0.45454545454545453,
      "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
      "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464,
      "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
      "mmlu_eval_accuracy_electrical_engineering": 0.375,
      "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
      "mmlu_eval_accuracy_formal_logic": 0.35714285714285715,
      "mmlu_eval_accuracy_global_facts": 0.5,
      "mmlu_eval_accuracy_high_school_biology": 0.34375,
      "mmlu_eval_accuracy_high_school_chemistry": 0.36363636363636365,
      "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
      "mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
      "mmlu_eval_accuracy_high_school_geography": 0.6818181818181818,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723,
      "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.34615384615384615,
      "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
      "mmlu_eval_accuracy_high_school_psychology": 0.7166666666666667,
      "mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
      "mmlu_eval_accuracy_high_school_us_history": 0.6818181818181818,
      "mmlu_eval_accuracy_high_school_world_history": 0.5384615384615384,
      "mmlu_eval_accuracy_human_aging": 0.6956521739130435,
      "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
      "mmlu_eval_accuracy_international_law": 0.7692307692307693,
      "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
      "mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
      "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
      "mmlu_eval_accuracy_management": 0.7272727272727273,
      "mmlu_eval_accuracy_marketing": 0.68,
      "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
      "mmlu_eval_accuracy_miscellaneous": 0.6627906976744186,
      "mmlu_eval_accuracy_moral_disputes": 0.5,
      "mmlu_eval_accuracy_moral_scenarios": 0.24,
      "mmlu_eval_accuracy_nutrition": 0.5757575757575758,
      "mmlu_eval_accuracy_philosophy": 0.4411764705882353,
      "mmlu_eval_accuracy_prehistory": 0.42857142857142855,
      "mmlu_eval_accuracy_professional_accounting": 0.3870967741935484,
      "mmlu_eval_accuracy_professional_law": 0.3588235294117647,
      "mmlu_eval_accuracy_professional_medicine": 0.45161290322580644,
      "mmlu_eval_accuracy_professional_psychology": 0.4057971014492754,
      "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
      "mmlu_eval_accuracy_security_studies": 0.5185185185185185,
      "mmlu_eval_accuracy_sociology": 0.5454545454545454,
      "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
      "mmlu_eval_accuracy_virology": 0.4444444444444444,
      "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
      "mmlu_loss": 0.9554785659084433,
      "step": 400
    },
    {
      "epoch": 0.28,
      "learning_rate": 0.0002,
      "loss": 0.8383,
      "step": 410
    },
    {
      "epoch": 0.29,
      "learning_rate": 0.0002,
      "loss": 0.8315,
      "step": 420
    },
    {
      "epoch": 0.3,
      "learning_rate": 0.0002,
      "loss": 0.8613,
      "step": 430
    },
    {
      "epoch": 0.3,
      "learning_rate": 0.0002,
      "loss": 0.865,
      "step": 440
    },
    {
      "epoch": 0.31,
      "learning_rate": 0.0002,
      "loss": 0.8028,
      "step": 450
    },
    {
      "epoch": 0.32,
      "learning_rate": 0.0002,
      "loss": 0.8557,
      "step": 460
    },
    {
      "epoch": 0.32,
      "learning_rate": 0.0002,
      "loss": 0.8834,
      "step": 470
    },
    {
      "epoch": 0.33,
      "learning_rate": 0.0002,
      "loss": 0.8468,
      "step": 480
    },
    {
      "epoch": 0.34,
      "learning_rate": 0.0002,
      "loss": 0.8556,
      "step": 490
    },
    {
      "epoch": 0.34,
      "learning_rate": 0.0002,
      "loss": 0.8591,
      "step": 500
    },
    {
      "epoch": 0.35,
      "learning_rate": 0.0002,
      "loss": 0.8683,
      "step": 510
    },
    {
      "epoch": 0.36,
      "learning_rate": 0.0002,
      "loss": 0.8278,
      "step": 520
    },
    {
      "epoch": 0.36,
      "learning_rate": 0.0002,
      "loss": 0.8208,
      "step": 530
    },
    {
      "epoch": 0.37,
      "learning_rate": 0.0002,
      "loss": 0.8372,
      "step": 540
    },
    {
      "epoch": 0.38,
      "learning_rate": 0.0002,
      "loss": 0.8144,
      "step": 550
    },
    {
      "epoch": 0.39,
      "learning_rate": 0.0002,
      "loss": 0.8783,
      "step": 560
    },
    {
      "epoch": 0.39,
      "learning_rate": 0.0002,
      "loss": 0.8337,
      "step": 570
    },
    {
      "epoch": 0.4,
      "learning_rate": 0.0002,
      "loss": 0.8572,
      "step": 580
    },
    {
      "epoch": 0.41,
      "learning_rate": 0.0002,
      "loss": 0.8275,
      "step": 590
    },
    {
      "epoch": 0.41,
      "learning_rate": 0.0002,
      "loss": 0.8599,
      "step": 600
    },
    {
      "epoch": 0.41,
      "eval_loss": 0.84308922290802,
      "eval_runtime": 189.8586,
      "eval_samples_per_second": 5.267,
      "eval_steps_per_second": 2.634,
      "step": 600
    },
    {
      "epoch": 0.41,
      "mmlu_eval_accuracy": 0.45447446268908714,
      "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
      "mmlu_eval_accuracy_anatomy": 0.5,
      "mmlu_eval_accuracy_astronomy": 0.375,
      "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
      "mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655,
      "mmlu_eval_accuracy_college_biology": 0.375,
      "mmlu_eval_accuracy_college_chemistry": 0.125,
      "mmlu_eval_accuracy_college_computer_science": 0.45454545454545453,
      "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
      "mmlu_eval_accuracy_college_medicine": 0.3181818181818182,
      "mmlu_eval_accuracy_college_physics": 0.45454545454545453,
      "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
      "mmlu_eval_accuracy_conceptual_physics": 0.34615384615384615,
      "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
      "mmlu_eval_accuracy_electrical_engineering": 0.375,
      "mmlu_eval_accuracy_elementary_mathematics": 0.3902439024390244,
      "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
      "mmlu_eval_accuracy_global_facts": 0.4,
      "mmlu_eval_accuracy_high_school_biology": 0.3125,
      "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091,
      "mmlu_eval_accuracy_high_school_computer_science": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
      "mmlu_eval_accuracy_high_school_geography": 0.7272727272727273,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.3023255813953488,
      "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.23076923076923078,
      "mmlu_eval_accuracy_high_school_physics": 0.35294117647058826,
      "mmlu_eval_accuracy_high_school_psychology": 0.6833333333333333,
      "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
      "mmlu_eval_accuracy_high_school_us_history": 0.7272727272727273,
      "mmlu_eval_accuracy_high_school_world_history": 0.5769230769230769,
      "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
      "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
      "mmlu_eval_accuracy_international_law": 0.6923076923076923,
      "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
      "mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
      "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
      "mmlu_eval_accuracy_management": 0.45454545454545453,
      "mmlu_eval_accuracy_marketing": 0.72,
      "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
      "mmlu_eval_accuracy_miscellaneous": 0.6511627906976745,
      "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
      "mmlu_eval_accuracy_moral_scenarios": 0.22,
      "mmlu_eval_accuracy_nutrition": 0.6363636363636364,
      "mmlu_eval_accuracy_philosophy": 0.5294117647058824,
      "mmlu_eval_accuracy_prehistory": 0.4,
      "mmlu_eval_accuracy_professional_accounting": 0.3548387096774194,
      "mmlu_eval_accuracy_professional_law": 0.3235294117647059,
      "mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
      "mmlu_eval_accuracy_professional_psychology": 0.43478260869565216,
      "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
      "mmlu_eval_accuracy_security_studies": 0.5185185185185185,
      "mmlu_eval_accuracy_sociology": 0.5454545454545454,
      "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
      "mmlu_eval_accuracy_virology": 0.5,
      "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
      "mmlu_loss": 0.9984549878082449,
      "step": 600
    },
    {
      "epoch": 0.42,
      "learning_rate": 0.0002,
      "loss": 0.8279,
      "step": 610
    },
    {
      "epoch": 0.43,
      "learning_rate": 0.0002,
      "loss": 0.8363,
      "step": 620
    },
    {
      "epoch": 0.43,
      "learning_rate": 0.0002,
      "loss": 0.8698,
      "step": 630
    },
    {
      "epoch": 0.44,
      "learning_rate": 0.0002,
      "loss": 0.8407,
      "step": 640
    },
    {
      "epoch": 0.45,
      "learning_rate": 0.0002,
      "loss": 0.8555,
      "step": 650
    },
    {
      "epoch": 0.45,
      "learning_rate": 0.0002,
      "loss": 0.8393,
      "step": 660
    },
    {
      "epoch": 0.46,
      "learning_rate": 0.0002,
      "loss": 0.8527,
      "step": 670
    },
    {
      "epoch": 0.47,
      "learning_rate": 0.0002,
      "loss": 0.8666,
      "step": 680
    },
    {
      "epoch": 0.47,
      "learning_rate": 0.0002,
      "loss": 0.8584,
      "step": 690
    },
    {
      "epoch": 0.48,
      "learning_rate": 0.0002,
      "loss": 0.8583,
      "step": 700
    },
    {
      "epoch": 0.49,
      "learning_rate": 0.0002,
      "loss": 0.8524,
      "step": 710
    },
    {
      "epoch": 0.5,
      "learning_rate": 0.0002,
      "loss": 0.8543,
      "step": 720
    },
    {
      "epoch": 0.5,
      "learning_rate": 0.0002,
      "loss": 0.8687,
      "step": 730
    },
    {
      "epoch": 0.51,
      "learning_rate": 0.0002,
      "loss": 0.8593,
      "step": 740
    },
    {
      "epoch": 0.52,
      "learning_rate": 0.0002,
      "loss": 0.8365,
      "step": 750
    },
    {
      "epoch": 0.52,
      "learning_rate": 0.0002,
      "loss": 0.8718,
      "step": 760
    },
    {
      "epoch": 0.53,
      "learning_rate": 0.0002,
      "loss": 0.8362,
      "step": 770
    },
    {
      "epoch": 0.54,
      "learning_rate": 0.0002,
      "loss": 0.8114,
      "step": 780
    },
    {
      "epoch": 0.54,
      "learning_rate": 0.0002,
      "loss": 0.8611,
      "step": 790
    },
    {
      "epoch": 0.55,
      "learning_rate": 0.0002,
      "loss": 0.8521,
      "step": 800
    },
    {
      "epoch": 0.55,
      "eval_loss": 0.8391241431236267,
      "eval_runtime": 189.8022,
      "eval_samples_per_second": 5.269,
      "eval_steps_per_second": 2.634,
      "step": 800
    },
    {
      "epoch": 0.55,
      "mmlu_eval_accuracy": 0.4694480562846655,
      "mmlu_eval_accuracy_abstract_algebra": 0.45454545454545453,
      "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
      "mmlu_eval_accuracy_astronomy": 0.3125,
      "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
      "mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655,
      "mmlu_eval_accuracy_college_biology": 0.5,
      "mmlu_eval_accuracy_college_chemistry": 0.25,
      "mmlu_eval_accuracy_college_computer_science": 0.45454545454545453,
      "mmlu_eval_accuracy_college_mathematics": 0.36363636363636365,
      "mmlu_eval_accuracy_college_medicine": 0.3181818181818182,
      "mmlu_eval_accuracy_college_physics": 0.45454545454545453,
      "mmlu_eval_accuracy_computer_security": 0.45454545454545453,
      "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464,
      "mmlu_eval_accuracy_econometrics": 0.25,
      "mmlu_eval_accuracy_electrical_engineering": 0.3125,
      "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
      "mmlu_eval_accuracy_formal_logic": 0.21428571428571427,
      "mmlu_eval_accuracy_global_facts": 0.5,
      "mmlu_eval_accuracy_high_school_biology": 0.4375,
      "mmlu_eval_accuracy_high_school_chemistry": 0.22727272727272727,
      "mmlu_eval_accuracy_high_school_computer_science": 0.4444444444444444,
      "mmlu_eval_accuracy_high_school_european_history": 0.4444444444444444,
      "mmlu_eval_accuracy_high_school_geography": 0.8636363636363636,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723,
      "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156,
      "mmlu_eval_accuracy_high_school_physics": 0.35294117647058826,
      "mmlu_eval_accuracy_high_school_psychology": 0.7166666666666667,
      "mmlu_eval_accuracy_high_school_statistics": 0.2608695652173913,
      "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
      "mmlu_eval_accuracy_high_school_world_history": 0.5384615384615384,
      "mmlu_eval_accuracy_human_aging": 0.6956521739130435,
      "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
      "mmlu_eval_accuracy_international_law": 0.8461538461538461,
      "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
      "mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
      "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
      "mmlu_eval_accuracy_management": 0.7272727272727273,
      "mmlu_eval_accuracy_marketing": 0.72,
      "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
      "mmlu_eval_accuracy_miscellaneous": 0.6627906976744186,
      "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
      "mmlu_eval_accuracy_moral_scenarios": 0.23,
      "mmlu_eval_accuracy_nutrition": 0.6666666666666666,
      "mmlu_eval_accuracy_philosophy": 0.4411764705882353,
      "mmlu_eval_accuracy_prehistory": 0.5428571428571428,
      "mmlu_eval_accuracy_professional_accounting": 0.22580645161290322,
      "mmlu_eval_accuracy_professional_law": 0.31176470588235294,
      "mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
      "mmlu_eval_accuracy_professional_psychology": 0.4057971014492754,
      "mmlu_eval_accuracy_public_relations": 0.5,
      "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
      "mmlu_eval_accuracy_sociology": 0.7272727272727273,
      "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
      "mmlu_eval_accuracy_virology": 0.3888888888888889,
      "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
      "mmlu_loss": 1.0093606002337006,
      "step": 800
    }
  ],
  "max_steps": 5000,
  "num_train_epochs": 4,
  "total_flos": 1.4473563545228083e+17,
  "trial_name": null,
  "trial_params": null
}