{
  "best_metric": 0.5406978130340576,
  "best_model_checkpoint": "./output_v2/7b_cluster016_Nous-Hermes-llama-2-7b_partitioned_v3_standardized_016/checkpoint-1000",
  "epoch": 1.670843776106934,
  "global_step": 1000,
  "is_hyper_param_search": false,
  "is_local_process_zero": true,
  "is_world_process_zero": true,
  "log_history": [
    {
      "epoch": 0.02,
      "learning_rate": 0.0002,
      "loss": 0.6709,
      "step": 10
    },
    {
      "epoch": 0.03,
      "learning_rate": 0.0002,
      "loss": 0.6086,
      "step": 20
    },
    {
      "epoch": 0.05,
      "learning_rate": 0.0002,
      "loss": 0.6457,
      "step": 30
    },
    {
      "epoch": 0.07,
      "learning_rate": 0.0002,
      "loss": 0.5722,
      "step": 40
    },
    {
      "epoch": 0.08,
      "learning_rate": 0.0002,
      "loss": 0.6039,
      "step": 50
    },
    {
      "epoch": 0.1,
      "learning_rate": 0.0002,
      "loss": 0.6079,
      "step": 60
    },
    {
      "epoch": 0.12,
      "learning_rate": 0.0002,
      "loss": 0.6261,
      "step": 70
    },
    {
      "epoch": 0.13,
      "learning_rate": 0.0002,
      "loss": 0.5876,
      "step": 80
    },
    {
      "epoch": 0.15,
      "learning_rate": 0.0002,
      "loss": 0.5645,
      "step": 90
    },
    {
      "epoch": 0.17,
      "learning_rate": 0.0002,
      "loss": 0.5902,
      "step": 100
    },
    {
      "epoch": 0.18,
      "learning_rate": 0.0002,
      "loss": 0.6008,
      "step": 110
    },
    {
      "epoch": 0.2,
      "learning_rate": 0.0002,
      "loss": 0.588,
      "step": 120
    },
    {
      "epoch": 0.22,
      "learning_rate": 0.0002,
      "loss": 0.6001,
      "step": 130
    },
    {
      "epoch": 0.23,
      "learning_rate": 0.0002,
      "loss": 0.5684,
      "step": 140
    },
    {
      "epoch": 0.25,
      "learning_rate": 0.0002,
      "loss": 0.5776,
      "step": 150
    },
    {
      "epoch": 0.27,
      "learning_rate": 0.0002,
      "loss": 0.5482,
      "step": 160
    },
    {
      "epoch": 0.28,
      "learning_rate": 0.0002,
      "loss": 0.5759,
      "step": 170
    },
    {
      "epoch": 0.3,
      "learning_rate": 0.0002,
      "loss": 0.5736,
      "step": 180
    },
    {
      "epoch": 0.32,
      "learning_rate": 0.0002,
      "loss": 0.5417,
      "step": 190
    },
    {
      "epoch": 0.33,
      "learning_rate": 0.0002,
      "loss": 0.5581,
      "step": 200
    },
    {
      "epoch": 0.33,
      "eval_loss": 0.5835912227630615,
      "eval_runtime": 210.8375,
      "eval_samples_per_second": 4.743,
      "eval_steps_per_second": 2.371,
      "step": 200
    },
    {
      "epoch": 0.33,
      "mmlu_eval_accuracy": 0.46615455952712886,
      "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
      "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
      "mmlu_eval_accuracy_astronomy": 0.4375,
      "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
      "mmlu_eval_accuracy_clinical_knowledge": 0.41379310344827586,
      "mmlu_eval_accuracy_college_biology": 0.5,
      "mmlu_eval_accuracy_college_chemistry": 0.125,
      "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
      "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
      "mmlu_eval_accuracy_college_medicine": 0.2727272727272727,
      "mmlu_eval_accuracy_college_physics": 0.45454545454545453,
      "mmlu_eval_accuracy_computer_security": 0.2727272727272727,
      "mmlu_eval_accuracy_conceptual_physics": 0.34615384615384615,
      "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
      "mmlu_eval_accuracy_electrical_engineering": 0.4375,
      "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
      "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
      "mmlu_eval_accuracy_global_facts": 0.6,
      "mmlu_eval_accuracy_high_school_biology": 0.34375,
      "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091,
      "mmlu_eval_accuracy_high_school_computer_science": 0.7777777777777778,
      "mmlu_eval_accuracy_high_school_european_history": 0.5,
      "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723,
      "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.4230769230769231,
      "mmlu_eval_accuracy_high_school_physics": 0.35294117647058826,
      "mmlu_eval_accuracy_high_school_psychology": 0.7,
      "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
      "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
      "mmlu_eval_accuracy_high_school_world_history": 0.5,
      "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
      "mmlu_eval_accuracy_human_sexuality": 0.5,
      "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": 0.2727272727272727,
      "mmlu_eval_accuracy_management": 0.45454545454545453,
      "mmlu_eval_accuracy_marketing": 0.76,
      "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
      "mmlu_eval_accuracy_miscellaneous": 0.686046511627907,
      "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
      "mmlu_eval_accuracy_moral_scenarios": 0.23,
      "mmlu_eval_accuracy_nutrition": 0.6060606060606061,
      "mmlu_eval_accuracy_philosophy": 0.4411764705882353,
      "mmlu_eval_accuracy_prehistory": 0.4857142857142857,
      "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
      "mmlu_eval_accuracy_professional_law": 0.3352941176470588,
      "mmlu_eval_accuracy_professional_medicine": 0.3870967741935484,
      "mmlu_eval_accuracy_professional_psychology": 0.36231884057971014,
      "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
      "mmlu_eval_accuracy_security_studies": 0.5925925925925926,
      "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": 1.1704803334048148,
      "step": 200
    },
    {
      "epoch": 0.35,
      "learning_rate": 0.0002,
      "loss": 0.5413,
      "step": 210
    },
    {
      "epoch": 0.37,
      "learning_rate": 0.0002,
      "loss": 0.5632,
      "step": 220
    },
    {
      "epoch": 0.38,
      "learning_rate": 0.0002,
      "loss": 0.5752,
      "step": 230
    },
    {
      "epoch": 0.4,
      "learning_rate": 0.0002,
      "loss": 0.5583,
      "step": 240
    },
    {
      "epoch": 0.42,
      "learning_rate": 0.0002,
      "loss": 0.5274,
      "step": 250
    },
    {
      "epoch": 0.43,
      "learning_rate": 0.0002,
      "loss": 0.6163,
      "step": 260
    },
    {
      "epoch": 0.45,
      "learning_rate": 0.0002,
      "loss": 0.5673,
      "step": 270
    },
    {
      "epoch": 0.47,
      "learning_rate": 0.0002,
      "loss": 0.5241,
      "step": 280
    },
    {
      "epoch": 0.48,
      "learning_rate": 0.0002,
      "loss": 0.5564,
      "step": 290
    },
    {
      "epoch": 0.5,
      "learning_rate": 0.0002,
      "loss": 0.5451,
      "step": 300
    },
    {
      "epoch": 0.52,
      "learning_rate": 0.0002,
      "loss": 0.5661,
      "step": 310
    },
    {
      "epoch": 0.53,
      "learning_rate": 0.0002,
      "loss": 0.5467,
      "step": 320
    },
    {
      "epoch": 0.55,
      "learning_rate": 0.0002,
      "loss": 0.5513,
      "step": 330
    },
    {
      "epoch": 0.57,
      "learning_rate": 0.0002,
      "loss": 0.5999,
      "step": 340
    },
    {
      "epoch": 0.58,
      "learning_rate": 0.0002,
      "loss": 0.5518,
      "step": 350
    },
    {
      "epoch": 0.6,
      "learning_rate": 0.0002,
      "loss": 0.4896,
      "step": 360
    },
    {
      "epoch": 0.62,
      "learning_rate": 0.0002,
      "loss": 0.5314,
      "step": 370
    },
    {
      "epoch": 0.63,
      "learning_rate": 0.0002,
      "loss": 0.5495,
      "step": 380
    },
    {
      "epoch": 0.65,
      "learning_rate": 0.0002,
      "loss": 0.553,
      "step": 390
    },
    {
      "epoch": 0.67,
      "learning_rate": 0.0002,
      "loss": 0.5324,
      "step": 400
    },
    {
      "epoch": 0.67,
      "eval_loss": 0.5613595843315125,
      "eval_runtime": 210.7546,
      "eval_samples_per_second": 4.745,
      "eval_steps_per_second": 2.372,
      "step": 400
    },
    {
      "epoch": 0.67,
      "mmlu_eval_accuracy": 0.47295524277138523,
      "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
      "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
      "mmlu_eval_accuracy_astronomy": 0.4375,
      "mmlu_eval_accuracy_business_ethics": 0.6363636363636364,
      "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": 0.2727272727272727,
      "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": 0.4375,
      "mmlu_eval_accuracy_elementary_mathematics": 0.36585365853658536,
      "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
      "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": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
      "mmlu_eval_accuracy_high_school_geography": 0.8181818181818182,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.3488372093023256,
      "mmlu_eval_accuracy_high_school_mathematics": 0.3448275862068966,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.38461538461538464,
      "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
      "mmlu_eval_accuracy_high_school_psychology": 0.7166666666666667,
      "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
      "mmlu_eval_accuracy_high_school_us_history": 0.7272727272727273,
      "mmlu_eval_accuracy_high_school_world_history": 0.5,
      "mmlu_eval_accuracy_human_aging": 0.6956521739130435,
      "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
      "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": 0.6363636363636364,
      "mmlu_eval_accuracy_marketing": 0.76,
      "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
      "mmlu_eval_accuracy_miscellaneous": 0.6744186046511628,
      "mmlu_eval_accuracy_moral_disputes": 0.42105263157894735,
      "mmlu_eval_accuracy_moral_scenarios": 0.23,
      "mmlu_eval_accuracy_nutrition": 0.6060606060606061,
      "mmlu_eval_accuracy_philosophy": 0.47058823529411764,
      "mmlu_eval_accuracy_prehistory": 0.4857142857142857,
      "mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
      "mmlu_eval_accuracy_professional_law": 0.35294117647058826,
      "mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
      "mmlu_eval_accuracy_professional_psychology": 0.37681159420289856,
      "mmlu_eval_accuracy_public_relations": 0.5,
      "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
      "mmlu_eval_accuracy_sociology": 0.6363636363636364,
      "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
      "mmlu_eval_accuracy_virology": 0.4444444444444444,
      "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
      "mmlu_loss": 1.1208655159366037,
      "step": 400
    },
    {
      "epoch": 0.69,
      "learning_rate": 0.0002,
      "loss": 0.5643,
      "step": 410
    },
    {
      "epoch": 0.7,
      "learning_rate": 0.0002,
      "loss": 0.5243,
      "step": 420
    },
    {
      "epoch": 0.72,
      "learning_rate": 0.0002,
      "loss": 0.5433,
      "step": 430
    },
    {
      "epoch": 0.74,
      "learning_rate": 0.0002,
      "loss": 0.5584,
      "step": 440
    },
    {
      "epoch": 0.75,
      "learning_rate": 0.0002,
      "loss": 0.5438,
      "step": 450
    },
    {
      "epoch": 0.77,
      "learning_rate": 0.0002,
      "loss": 0.5203,
      "step": 460
    },
    {
      "epoch": 0.79,
      "learning_rate": 0.0002,
      "loss": 0.5328,
      "step": 470
    },
    {
      "epoch": 0.8,
      "learning_rate": 0.0002,
      "loss": 0.5204,
      "step": 480
    },
    {
      "epoch": 0.82,
      "learning_rate": 0.0002,
      "loss": 0.5194,
      "step": 490
    },
    {
      "epoch": 0.84,
      "learning_rate": 0.0002,
      "loss": 0.5325,
      "step": 500
    },
    {
      "epoch": 0.85,
      "learning_rate": 0.0002,
      "loss": 0.5407,
      "step": 510
    },
    {
      "epoch": 0.87,
      "learning_rate": 0.0002,
      "loss": 0.4747,
      "step": 520
    },
    {
      "epoch": 0.89,
      "learning_rate": 0.0002,
      "loss": 0.5048,
      "step": 530
    },
    {
      "epoch": 0.9,
      "learning_rate": 0.0002,
      "loss": 0.5533,
      "step": 540
    },
    {
      "epoch": 0.92,
      "learning_rate": 0.0002,
      "loss": 0.5219,
      "step": 550
    },
    {
      "epoch": 0.94,
      "learning_rate": 0.0002,
      "loss": 0.5357,
      "step": 560
    },
    {
      "epoch": 0.95,
      "learning_rate": 0.0002,
      "loss": 0.5327,
      "step": 570
    },
    {
      "epoch": 0.97,
      "learning_rate": 0.0002,
      "loss": 0.492,
      "step": 580
    },
    {
      "epoch": 0.99,
      "learning_rate": 0.0002,
      "loss": 0.5312,
      "step": 590
    },
    {
      "epoch": 1.0,
      "learning_rate": 0.0002,
      "loss": 0.5238,
      "step": 600
    },
    {
      "epoch": 1.0,
      "eval_loss": 0.5487588047981262,
      "eval_runtime": 211.0529,
      "eval_samples_per_second": 4.738,
      "eval_steps_per_second": 2.369,
      "step": 600
    },
    {
      "epoch": 1.0,
      "mmlu_eval_accuracy": 0.4657057894438228,
      "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
      "mmlu_eval_accuracy_anatomy": 0.5,
      "mmlu_eval_accuracy_astronomy": 0.4375,
      "mmlu_eval_accuracy_business_ethics": 0.6363636363636364,
      "mmlu_eval_accuracy_clinical_knowledge": 0.41379310344827586,
      "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": 0.3076923076923077,
      "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
      "mmlu_eval_accuracy_electrical_engineering": 0.4375,
      "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
      "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
      "mmlu_eval_accuracy_global_facts": 0.5,
      "mmlu_eval_accuracy_high_school_biology": 0.34375,
      "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091,
      "mmlu_eval_accuracy_high_school_computer_science": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723,
      "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.38461538461538464,
      "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
      "mmlu_eval_accuracy_high_school_psychology": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
      "mmlu_eval_accuracy_high_school_us_history": 0.7272727272727273,
      "mmlu_eval_accuracy_high_school_world_history": 0.46153846153846156,
      "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
      "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
      "mmlu_eval_accuracy_international_law": 0.8461538461538461,
      "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
      "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": 0.6627906976744186,
      "mmlu_eval_accuracy_moral_disputes": 0.39473684210526316,
      "mmlu_eval_accuracy_moral_scenarios": 0.24,
      "mmlu_eval_accuracy_nutrition": 0.5757575757575758,
      "mmlu_eval_accuracy_philosophy": 0.5,
      "mmlu_eval_accuracy_prehistory": 0.45714285714285713,
      "mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
      "mmlu_eval_accuracy_professional_law": 0.3352941176470588,
      "mmlu_eval_accuracy_professional_medicine": 0.3870967741935484,
      "mmlu_eval_accuracy_professional_psychology": 0.391304347826087,
      "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
      "mmlu_eval_accuracy_security_studies": 0.5185185185185185,
      "mmlu_eval_accuracy_sociology": 0.6818181818181818,
      "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
      "mmlu_eval_accuracy_virology": 0.5,
      "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
      "mmlu_loss": 1.2064378902744064,
      "step": 600
    },
    {
      "epoch": 1.02,
      "learning_rate": 0.0002,
      "loss": 0.4304,
      "step": 610
    },
    {
      "epoch": 1.04,
      "learning_rate": 0.0002,
      "loss": 0.466,
      "step": 620
    },
    {
      "epoch": 1.05,
      "learning_rate": 0.0002,
      "loss": 0.4934,
      "step": 630
    },
    {
      "epoch": 1.07,
      "learning_rate": 0.0002,
      "loss": 0.4605,
      "step": 640
    },
    {
      "epoch": 1.09,
      "learning_rate": 0.0002,
      "loss": 0.4799,
      "step": 650
    },
    {
      "epoch": 1.1,
      "learning_rate": 0.0002,
      "loss": 0.4572,
      "step": 660
    },
    {
      "epoch": 1.12,
      "learning_rate": 0.0002,
      "loss": 0.4398,
      "step": 670
    },
    {
      "epoch": 1.14,
      "learning_rate": 0.0002,
      "loss": 0.4673,
      "step": 680
    },
    {
      "epoch": 1.15,
      "learning_rate": 0.0002,
      "loss": 0.5008,
      "step": 690
    },
    {
      "epoch": 1.17,
      "learning_rate": 0.0002,
      "loss": 0.4832,
      "step": 700
    },
    {
      "epoch": 1.19,
      "learning_rate": 0.0002,
      "loss": 0.4558,
      "step": 710
    },
    {
      "epoch": 1.2,
      "learning_rate": 0.0002,
      "loss": 0.4661,
      "step": 720
    },
    {
      "epoch": 1.22,
      "learning_rate": 0.0002,
      "loss": 0.4483,
      "step": 730
    },
    {
      "epoch": 1.24,
      "learning_rate": 0.0002,
      "loss": 0.5047,
      "step": 740
    },
    {
      "epoch": 1.25,
      "learning_rate": 0.0002,
      "loss": 0.479,
      "step": 750
    },
    {
      "epoch": 1.27,
      "learning_rate": 0.0002,
      "loss": 0.4975,
      "step": 760
    },
    {
      "epoch": 1.29,
      "learning_rate": 0.0002,
      "loss": 0.4797,
      "step": 770
    },
    {
      "epoch": 1.3,
      "learning_rate": 0.0002,
      "loss": 0.4884,
      "step": 780
    },
    {
      "epoch": 1.32,
      "learning_rate": 0.0002,
      "loss": 0.4631,
      "step": 790
    },
    {
      "epoch": 1.34,
      "learning_rate": 0.0002,
      "loss": 0.4541,
      "step": 800
    },
    {
      "epoch": 1.34,
      "eval_loss": 0.545791745185852,
      "eval_runtime": 211.0641,
      "eval_samples_per_second": 4.738,
      "eval_steps_per_second": 2.369,
      "step": 800
    },
    {
      "epoch": 1.34,
      "mmlu_eval_accuracy": 0.46218071540689526,
      "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
      "mmlu_eval_accuracy_anatomy": 0.5,
      "mmlu_eval_accuracy_astronomy": 0.375,
      "mmlu_eval_accuracy_business_ethics": 0.6363636363636364,
      "mmlu_eval_accuracy_clinical_knowledge": 0.41379310344827586,
      "mmlu_eval_accuracy_college_biology": 0.4375,
      "mmlu_eval_accuracy_college_chemistry": 0.125,
      "mmlu_eval_accuracy_college_computer_science": 0.5454545454545454,
      "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": 0.2727272727272727,
      "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": 0.34146341463414637,
      "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
      "mmlu_eval_accuracy_global_facts": 0.5,
      "mmlu_eval_accuracy_high_school_biology": 0.40625,
      "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091,
      "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
      "mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
      "mmlu_eval_accuracy_high_school_geography": 0.7272727272727273,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.3488372093023256,
      "mmlu_eval_accuracy_high_school_mathematics": 0.3103448275862069,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.38461538461538464,
      "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
      "mmlu_eval_accuracy_high_school_psychology": 0.6833333333333333,
      "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
      "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": 0.5833333333333334,
      "mmlu_eval_accuracy_international_law": 0.7692307692307693,
      "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
      "mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
      "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
      "mmlu_eval_accuracy_management": 0.6363636363636364,
      "mmlu_eval_accuracy_marketing": 0.72,
      "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
      "mmlu_eval_accuracy_miscellaneous": 0.6627906976744186,
      "mmlu_eval_accuracy_moral_disputes": 0.39473684210526316,
      "mmlu_eval_accuracy_moral_scenarios": 0.23,
      "mmlu_eval_accuracy_nutrition": 0.6363636363636364,
      "mmlu_eval_accuracy_philosophy": 0.5294117647058824,
      "mmlu_eval_accuracy_prehistory": 0.45714285714285713,
      "mmlu_eval_accuracy_professional_accounting": 0.22580645161290322,
      "mmlu_eval_accuracy_professional_law": 0.3588235294117647,
      "mmlu_eval_accuracy_professional_medicine": 0.3548387096774194,
      "mmlu_eval_accuracy_professional_psychology": 0.4057971014492754,
      "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
      "mmlu_eval_accuracy_security_studies": 0.5555555555555556,
      "mmlu_eval_accuracy_sociology": 0.5909090909090909,
      "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
      "mmlu_eval_accuracy_virology": 0.4444444444444444,
      "mmlu_eval_accuracy_world_religions": 0.7894736842105263,
      "mmlu_loss": 1.1216171698610715,
      "step": 800
    },
    {
      "epoch": 1.35,
      "learning_rate": 0.0002,
      "loss": 0.4589,
      "step": 810
    },
    {
      "epoch": 1.37,
      "learning_rate": 0.0002,
      "loss": 0.4307,
      "step": 820
    },
    {
      "epoch": 1.39,
      "learning_rate": 0.0002,
      "loss": 0.4653,
      "step": 830
    },
    {
      "epoch": 1.4,
      "learning_rate": 0.0002,
      "loss": 0.4843,
      "step": 840
    },
    {
      "epoch": 1.42,
      "learning_rate": 0.0002,
      "loss": 0.4851,
      "step": 850
    },
    {
      "epoch": 1.44,
      "learning_rate": 0.0002,
      "loss": 0.458,
      "step": 860
    },
    {
      "epoch": 1.45,
      "learning_rate": 0.0002,
      "loss": 0.4529,
      "step": 870
    },
    {
      "epoch": 1.47,
      "learning_rate": 0.0002,
      "loss": 0.4881,
      "step": 880
    },
    {
      "epoch": 1.49,
      "learning_rate": 0.0002,
      "loss": 0.4789,
      "step": 890
    },
    {
      "epoch": 1.5,
      "learning_rate": 0.0002,
      "loss": 0.4716,
      "step": 900
    },
    {
      "epoch": 1.52,
      "learning_rate": 0.0002,
      "loss": 0.4771,
      "step": 910
    },
    {
      "epoch": 1.54,
      "learning_rate": 0.0002,
      "loss": 0.4775,
      "step": 920
    },
    {
      "epoch": 1.55,
      "learning_rate": 0.0002,
      "loss": 0.4701,
      "step": 930
    },
    {
      "epoch": 1.57,
      "learning_rate": 0.0002,
      "loss": 0.4855,
      "step": 940
    },
    {
      "epoch": 1.59,
      "learning_rate": 0.0002,
      "loss": 0.4625,
      "step": 950
    },
    {
      "epoch": 1.6,
      "learning_rate": 0.0002,
      "loss": 0.4505,
      "step": 960
    },
    {
      "epoch": 1.62,
      "learning_rate": 0.0002,
      "loss": 0.4637,
      "step": 970
    },
    {
      "epoch": 1.64,
      "learning_rate": 0.0002,
      "loss": 0.4672,
      "step": 980
    },
    {
      "epoch": 1.65,
      "learning_rate": 0.0002,
      "loss": 0.4549,
      "step": 990
    },
    {
      "epoch": 1.67,
      "learning_rate": 0.0002,
      "loss": 0.465,
      "step": 1000
    },
    {
      "epoch": 1.67,
      "eval_loss": 0.5406978130340576,
      "eval_runtime": 211.1574,
      "eval_samples_per_second": 4.736,
      "eval_steps_per_second": 2.368,
      "step": 1000
    },
    {
      "epoch": 1.67,
      "mmlu_eval_accuracy": 0.45948472060928486,
      "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
      "mmlu_eval_accuracy_anatomy": 0.5,
      "mmlu_eval_accuracy_astronomy": 0.4375,
      "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
      "mmlu_eval_accuracy_clinical_knowledge": 0.41379310344827586,
      "mmlu_eval_accuracy_college_biology": 0.3125,
      "mmlu_eval_accuracy_college_chemistry": 0.25,
      "mmlu_eval_accuracy_college_computer_science": 0.45454545454545453,
      "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
      "mmlu_eval_accuracy_college_medicine": 0.3181818181818182,
      "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
      "mmlu_eval_accuracy_computer_security": 0.2727272727272727,
      "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464,
      "mmlu_eval_accuracy_econometrics": 0.08333333333333333,
      "mmlu_eval_accuracy_electrical_engineering": 0.375,
      "mmlu_eval_accuracy_elementary_mathematics": 0.3170731707317073,
      "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
      "mmlu_eval_accuracy_global_facts": 0.4,
      "mmlu_eval_accuracy_high_school_biology": 0.375,
      "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": 0.7272727272727273,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723,
      "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.5,
      "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
      "mmlu_eval_accuracy_high_school_psychology": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
      "mmlu_eval_accuracy_high_school_us_history": 0.6818181818181818,
      "mmlu_eval_accuracy_high_school_world_history": 0.5,
      "mmlu_eval_accuracy_human_aging": 0.6086956521739131,
      "mmlu_eval_accuracy_human_sexuality": 0.6666666666666666,
      "mmlu_eval_accuracy_international_law": 0.7692307692307693,
      "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
      "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
      "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
      "mmlu_eval_accuracy_management": 0.7272727272727273,
      "mmlu_eval_accuracy_marketing": 0.8,
      "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
      "mmlu_eval_accuracy_miscellaneous": 0.6744186046511628,
      "mmlu_eval_accuracy_moral_disputes": 0.39473684210526316,
      "mmlu_eval_accuracy_moral_scenarios": 0.24,
      "mmlu_eval_accuracy_nutrition": 0.6363636363636364,
      "mmlu_eval_accuracy_philosophy": 0.5,
      "mmlu_eval_accuracy_prehistory": 0.4,
      "mmlu_eval_accuracy_professional_accounting": 0.1935483870967742,
      "mmlu_eval_accuracy_professional_law": 0.29411764705882354,
      "mmlu_eval_accuracy_professional_medicine": 0.3548387096774194,
      "mmlu_eval_accuracy_professional_psychology": 0.391304347826087,
      "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
      "mmlu_eval_accuracy_security_studies": 0.5555555555555556,
      "mmlu_eval_accuracy_sociology": 0.6363636363636364,
      "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
      "mmlu_eval_accuracy_virology": 0.5,
      "mmlu_eval_accuracy_world_religions": 0.8421052631578947,
      "mmlu_loss": 1.0519140656094015,
      "step": 1000
    }
  ],
  "max_steps": 5000,
  "num_train_epochs": 9,
  "total_flos": 2.480606046133125e+17,
  "trial_name": null,
  "trial_params": null
}