{
  "best_metric": 0.48671162128448486,
  "best_model_checkpoint": "./output_v2/7b_cluster09_Nous-Hermes-llama-2-7b_partitioned_v3_standardized_09/checkpoint-1600",
  "epoch": 2.7127003699136867,
  "global_step": 2200,
  "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": 0.597,
      "step": 10
    },
    {
      "epoch": 0.02,
      "learning_rate": 0.0002,
      "loss": 0.5778,
      "step": 20
    },
    {
      "epoch": 0.04,
      "learning_rate": 0.0002,
      "loss": 0.5677,
      "step": 30
    },
    {
      "epoch": 0.05,
      "learning_rate": 0.0002,
      "loss": 0.5528,
      "step": 40
    },
    {
      "epoch": 0.06,
      "learning_rate": 0.0002,
      "loss": 0.5558,
      "step": 50
    },
    {
      "epoch": 0.07,
      "learning_rate": 0.0002,
      "loss": 0.5571,
      "step": 60
    },
    {
      "epoch": 0.09,
      "learning_rate": 0.0002,
      "loss": 0.5499,
      "step": 70
    },
    {
      "epoch": 0.1,
      "learning_rate": 0.0002,
      "loss": 0.5491,
      "step": 80
    },
    {
      "epoch": 0.11,
      "learning_rate": 0.0002,
      "loss": 0.5407,
      "step": 90
    },
    {
      "epoch": 0.12,
      "learning_rate": 0.0002,
      "loss": 0.5492,
      "step": 100
    },
    {
      "epoch": 0.14,
      "learning_rate": 0.0002,
      "loss": 0.5258,
      "step": 110
    },
    {
      "epoch": 0.15,
      "learning_rate": 0.0002,
      "loss": 0.5217,
      "step": 120
    },
    {
      "epoch": 0.16,
      "learning_rate": 0.0002,
      "loss": 0.538,
      "step": 130
    },
    {
      "epoch": 0.17,
      "learning_rate": 0.0002,
      "loss": 0.5265,
      "step": 140
    },
    {
      "epoch": 0.18,
      "learning_rate": 0.0002,
      "loss": 0.5344,
      "step": 150
    },
    {
      "epoch": 0.2,
      "learning_rate": 0.0002,
      "loss": 0.5361,
      "step": 160
    },
    {
      "epoch": 0.21,
      "learning_rate": 0.0002,
      "loss": 0.5186,
      "step": 170
    },
    {
      "epoch": 0.22,
      "learning_rate": 0.0002,
      "loss": 0.5312,
      "step": 180
    },
    {
      "epoch": 0.23,
      "learning_rate": 0.0002,
      "loss": 0.5395,
      "step": 190
    },
    {
      "epoch": 0.25,
      "learning_rate": 0.0002,
      "loss": 0.5399,
      "step": 200
    },
    {
      "epoch": 0.25,
      "eval_loss": 0.533891499042511,
      "eval_runtime": 249.6236,
      "eval_samples_per_second": 4.006,
      "eval_steps_per_second": 2.003,
      "step": 200
    },
    {
      "epoch": 0.25,
      "mmlu_eval_accuracy": 0.46207163729626294,
      "mmlu_eval_accuracy_abstract_algebra": 0.09090909090909091,
      "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
      "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": 0.36363636363636365,
      "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": 0.36585365853658536,
      "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": 0.45454545454545453,
      "mmlu_eval_accuracy_high_school_computer_science": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
      "mmlu_eval_accuracy_high_school_geography": 0.6363636363636364,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723,
      "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.4230769230769231,
      "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
      "mmlu_eval_accuracy_high_school_psychology": 0.7333333333333333,
      "mmlu_eval_accuracy_high_school_statistics": 0.2608695652173913,
      "mmlu_eval_accuracy_high_school_us_history": 0.7272727272727273,
      "mmlu_eval_accuracy_high_school_world_history": 0.5384615384615384,
      "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": 0.45454545454545453,
      "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": 0.6744186046511628,
      "mmlu_eval_accuracy_moral_disputes": 0.5,
      "mmlu_eval_accuracy_moral_scenarios": 0.24,
      "mmlu_eval_accuracy_nutrition": 0.6060606060606061,
      "mmlu_eval_accuracy_philosophy": 0.47058823529411764,
      "mmlu_eval_accuracy_prehistory": 0.4857142857142857,
      "mmlu_eval_accuracy_professional_accounting": 0.3225806451612903,
      "mmlu_eval_accuracy_professional_law": 0.34705882352941175,
      "mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
      "mmlu_eval_accuracy_professional_psychology": 0.37681159420289856,
      "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
      "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
      "mmlu_eval_accuracy_sociology": 0.6363636363636364,
      "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
      "mmlu_eval_accuracy_virology": 0.3888888888888889,
      "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
      "mmlu_loss": 1.267449478023046,
      "step": 200
    },
    {
      "epoch": 0.26,
      "learning_rate": 0.0002,
      "loss": 0.524,
      "step": 210
    },
    {
      "epoch": 0.27,
      "learning_rate": 0.0002,
      "loss": 0.5484,
      "step": 220
    },
    {
      "epoch": 0.28,
      "learning_rate": 0.0002,
      "loss": 0.5247,
      "step": 230
    },
    {
      "epoch": 0.3,
      "learning_rate": 0.0002,
      "loss": 0.5305,
      "step": 240
    },
    {
      "epoch": 0.31,
      "learning_rate": 0.0002,
      "loss": 0.5179,
      "step": 250
    },
    {
      "epoch": 0.32,
      "learning_rate": 0.0002,
      "loss": 0.5408,
      "step": 260
    },
    {
      "epoch": 0.33,
      "learning_rate": 0.0002,
      "loss": 0.5472,
      "step": 270
    },
    {
      "epoch": 0.35,
      "learning_rate": 0.0002,
      "loss": 0.5136,
      "step": 280
    },
    {
      "epoch": 0.36,
      "learning_rate": 0.0002,
      "loss": 0.5262,
      "step": 290
    },
    {
      "epoch": 0.37,
      "learning_rate": 0.0002,
      "loss": 0.5361,
      "step": 300
    },
    {
      "epoch": 0.38,
      "learning_rate": 0.0002,
      "loss": 0.5007,
      "step": 310
    },
    {
      "epoch": 0.39,
      "learning_rate": 0.0002,
      "loss": 0.5211,
      "step": 320
    },
    {
      "epoch": 0.41,
      "learning_rate": 0.0002,
      "loss": 0.5217,
      "step": 330
    },
    {
      "epoch": 0.42,
      "learning_rate": 0.0002,
      "loss": 0.5337,
      "step": 340
    },
    {
      "epoch": 0.43,
      "learning_rate": 0.0002,
      "loss": 0.5113,
      "step": 350
    },
    {
      "epoch": 0.44,
      "learning_rate": 0.0002,
      "loss": 0.518,
      "step": 360
    },
    {
      "epoch": 0.46,
      "learning_rate": 0.0002,
      "loss": 0.5151,
      "step": 370
    },
    {
      "epoch": 0.47,
      "learning_rate": 0.0002,
      "loss": 0.5133,
      "step": 380
    },
    {
      "epoch": 0.48,
      "learning_rate": 0.0002,
      "loss": 0.5083,
      "step": 390
    },
    {
      "epoch": 0.49,
      "learning_rate": 0.0002,
      "loss": 0.5235,
      "step": 400
    },
    {
      "epoch": 0.49,
      "eval_loss": 0.5213926434516907,
      "eval_runtime": 249.5749,
      "eval_samples_per_second": 4.007,
      "eval_steps_per_second": 2.003,
      "step": 400
    },
    {
      "epoch": 0.49,
      "mmlu_eval_accuracy": 0.45812855653406065,
      "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
      "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
      "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": 0.36363636363636365,
      "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": 0.2682926829268293,
      "mmlu_eval_accuracy_formal_logic": 0.21428571428571427,
      "mmlu_eval_accuracy_global_facts": 0.6,
      "mmlu_eval_accuracy_high_school_biology": 0.375,
      "mmlu_eval_accuracy_high_school_chemistry": 0.45454545454545453,
      "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
      "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
      "mmlu_eval_accuracy_high_school_geography": 0.6818181818181818,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723,
      "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.4230769230769231,
      "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
      "mmlu_eval_accuracy_high_school_psychology": 0.75,
      "mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
      "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
      "mmlu_eval_accuracy_high_school_world_history": 0.5384615384615384,
      "mmlu_eval_accuracy_human_aging": 0.7391304347826086,
      "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
      "mmlu_eval_accuracy_international_law": 0.6923076923076923,
      "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
      "mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
      "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
      "mmlu_eval_accuracy_management": 0.45454545454545453,
      "mmlu_eval_accuracy_marketing": 0.8,
      "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": 0.24,
      "mmlu_eval_accuracy_nutrition": 0.6060606060606061,
      "mmlu_eval_accuracy_philosophy": 0.4411764705882353,
      "mmlu_eval_accuracy_prehistory": 0.5428571428571428,
      "mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
      "mmlu_eval_accuracy_professional_law": 0.3352941176470588,
      "mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
      "mmlu_eval_accuracy_professional_psychology": 0.36231884057971014,
      "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
      "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": 0.3333333333333333,
      "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
      "mmlu_loss": 1.1127305320092031,
      "step": 400
    },
    {
      "epoch": 0.51,
      "learning_rate": 0.0002,
      "loss": 0.5194,
      "step": 410
    },
    {
      "epoch": 0.52,
      "learning_rate": 0.0002,
      "loss": 0.5279,
      "step": 420
    },
    {
      "epoch": 0.53,
      "learning_rate": 0.0002,
      "loss": 0.5105,
      "step": 430
    },
    {
      "epoch": 0.54,
      "learning_rate": 0.0002,
      "loss": 0.5427,
      "step": 440
    },
    {
      "epoch": 0.55,
      "learning_rate": 0.0002,
      "loss": 0.5276,
      "step": 450
    },
    {
      "epoch": 0.57,
      "learning_rate": 0.0002,
      "loss": 0.4865,
      "step": 460
    },
    {
      "epoch": 0.58,
      "learning_rate": 0.0002,
      "loss": 0.5161,
      "step": 470
    },
    {
      "epoch": 0.59,
      "learning_rate": 0.0002,
      "loss": 0.513,
      "step": 480
    },
    {
      "epoch": 0.6,
      "learning_rate": 0.0002,
      "loss": 0.5284,
      "step": 490
    },
    {
      "epoch": 0.62,
      "learning_rate": 0.0002,
      "loss": 0.5101,
      "step": 500
    },
    {
      "epoch": 0.63,
      "learning_rate": 0.0002,
      "loss": 0.5218,
      "step": 510
    },
    {
      "epoch": 0.64,
      "learning_rate": 0.0002,
      "loss": 0.5087,
      "step": 520
    },
    {
      "epoch": 0.65,
      "learning_rate": 0.0002,
      "loss": 0.5157,
      "step": 530
    },
    {
      "epoch": 0.67,
      "learning_rate": 0.0002,
      "loss": 0.501,
      "step": 540
    },
    {
      "epoch": 0.68,
      "learning_rate": 0.0002,
      "loss": 0.508,
      "step": 550
    },
    {
      "epoch": 0.69,
      "learning_rate": 0.0002,
      "loss": 0.5199,
      "step": 560
    },
    {
      "epoch": 0.7,
      "learning_rate": 0.0002,
      "loss": 0.5043,
      "step": 570
    },
    {
      "epoch": 0.72,
      "learning_rate": 0.0002,
      "loss": 0.5069,
      "step": 580
    },
    {
      "epoch": 0.73,
      "learning_rate": 0.0002,
      "loss": 0.5258,
      "step": 590
    },
    {
      "epoch": 0.74,
      "learning_rate": 0.0002,
      "loss": 0.5189,
      "step": 600
    },
    {
      "epoch": 0.74,
      "eval_loss": 0.5119001865386963,
      "eval_runtime": 249.8867,
      "eval_samples_per_second": 4.002,
      "eval_steps_per_second": 2.001,
      "step": 600
    },
    {
      "epoch": 0.74,
      "mmlu_eval_accuracy": 0.45806114323766334,
      "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
      "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
      "mmlu_eval_accuracy_astronomy": 0.4375,
      "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": 0.36363636363636365,
      "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": 0.36363636363636365,
      "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464,
      "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
      "mmlu_eval_accuracy_electrical_engineering": 0.3125,
      "mmlu_eval_accuracy_elementary_mathematics": 0.3170731707317073,
      "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
      "mmlu_eval_accuracy_global_facts": 0.6,
      "mmlu_eval_accuracy_high_school_biology": 0.375,
      "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091,
      "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
      "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
      "mmlu_eval_accuracy_high_school_geography": 0.6818181818181818,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.3488372093023256,
      "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.4230769230769231,
      "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
      "mmlu_eval_accuracy_high_school_psychology": 0.7666666666666667,
      "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
      "mmlu_eval_accuracy_high_school_us_history": 0.7272727272727273,
      "mmlu_eval_accuracy_high_school_world_history": 0.5769230769230769,
      "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": 0.45454545454545453,
      "mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
      "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
      "mmlu_eval_accuracy_management": 0.5454545454545454,
      "mmlu_eval_accuracy_marketing": 0.8,
      "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": 0.4117647058823529,
      "mmlu_eval_accuracy_prehistory": 0.4857142857142857,
      "mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
      "mmlu_eval_accuracy_professional_law": 0.3352941176470588,
      "mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
      "mmlu_eval_accuracy_professional_psychology": 0.36231884057971014,
      "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
      "mmlu_eval_accuracy_security_studies": 0.5185185185185185,
      "mmlu_eval_accuracy_sociology": 0.6363636363636364,
      "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
      "mmlu_eval_accuracy_virology": 0.3333333333333333,
      "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
      "mmlu_loss": 1.1718710024425318,
      "step": 600
    },
    {
      "epoch": 0.75,
      "learning_rate": 0.0002,
      "loss": 0.5234,
      "step": 610
    },
    {
      "epoch": 0.76,
      "learning_rate": 0.0002,
      "loss": 0.5205,
      "step": 620
    },
    {
      "epoch": 0.78,
      "learning_rate": 0.0002,
      "loss": 0.5146,
      "step": 630
    },
    {
      "epoch": 0.79,
      "learning_rate": 0.0002,
      "loss": 0.5094,
      "step": 640
    },
    {
      "epoch": 0.8,
      "learning_rate": 0.0002,
      "loss": 0.4959,
      "step": 650
    },
    {
      "epoch": 0.81,
      "learning_rate": 0.0002,
      "loss": 0.5001,
      "step": 660
    },
    {
      "epoch": 0.83,
      "learning_rate": 0.0002,
      "loss": 0.5007,
      "step": 670
    },
    {
      "epoch": 0.84,
      "learning_rate": 0.0002,
      "loss": 0.5029,
      "step": 680
    },
    {
      "epoch": 0.85,
      "learning_rate": 0.0002,
      "loss": 0.5143,
      "step": 690
    },
    {
      "epoch": 0.86,
      "learning_rate": 0.0002,
      "loss": 0.4983,
      "step": 700
    },
    {
      "epoch": 0.88,
      "learning_rate": 0.0002,
      "loss": 0.4995,
      "step": 710
    },
    {
      "epoch": 0.89,
      "learning_rate": 0.0002,
      "loss": 0.5072,
      "step": 720
    },
    {
      "epoch": 0.9,
      "learning_rate": 0.0002,
      "loss": 0.499,
      "step": 730
    },
    {
      "epoch": 0.91,
      "learning_rate": 0.0002,
      "loss": 0.505,
      "step": 740
    },
    {
      "epoch": 0.92,
      "learning_rate": 0.0002,
      "loss": 0.4917,
      "step": 750
    },
    {
      "epoch": 0.94,
      "learning_rate": 0.0002,
      "loss": 0.4983,
      "step": 760
    },
    {
      "epoch": 0.95,
      "learning_rate": 0.0002,
      "loss": 0.4946,
      "step": 770
    },
    {
      "epoch": 0.96,
      "learning_rate": 0.0002,
      "loss": 0.4931,
      "step": 780
    },
    {
      "epoch": 0.97,
      "learning_rate": 0.0002,
      "loss": 0.4836,
      "step": 790
    },
    {
      "epoch": 0.99,
      "learning_rate": 0.0002,
      "loss": 0.5001,
      "step": 800
    },
    {
      "epoch": 0.99,
      "eval_loss": 0.5022817254066467,
      "eval_runtime": 249.7465,
      "eval_samples_per_second": 4.004,
      "eval_steps_per_second": 2.002,
      "step": 800
    },
    {
      "epoch": 0.99,
      "mmlu_eval_accuracy": 0.45223086902107806,
      "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
      "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
      "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": 0.4375,
      "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": 0.36363636363636365,
      "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": 0.2926829268292683,
      "mmlu_eval_accuracy_formal_logic": 0.21428571428571427,
      "mmlu_eval_accuracy_global_facts": 0.5,
      "mmlu_eval_accuracy_high_school_biology": 0.34375,
      "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
      "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
      "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
      "mmlu_eval_accuracy_high_school_geography": 0.6363636363636364,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.3488372093023256,
      "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.4230769230769231,
      "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
      "mmlu_eval_accuracy_high_school_psychology": 0.75,
      "mmlu_eval_accuracy_high_school_statistics": 0.2608695652173913,
      "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
      "mmlu_eval_accuracy_high_school_world_history": 0.5769230769230769,
      "mmlu_eval_accuracy_human_aging": 0.7391304347826086,
      "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
      "mmlu_eval_accuracy_international_law": 0.6923076923076923,
      "mmlu_eval_accuracy_jurisprudence": 0.5454545454545454,
      "mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
      "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
      "mmlu_eval_accuracy_management": 0.45454545454545453,
      "mmlu_eval_accuracy_marketing": 0.8,
      "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
      "mmlu_eval_accuracy_miscellaneous": 0.6395348837209303,
      "mmlu_eval_accuracy_moral_disputes": 0.5,
      "mmlu_eval_accuracy_moral_scenarios": 0.24,
      "mmlu_eval_accuracy_nutrition": 0.6060606060606061,
      "mmlu_eval_accuracy_philosophy": 0.4117647058823529,
      "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": 0.36231884057971014,
      "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
      "mmlu_eval_accuracy_security_studies": 0.5185185185185185,
      "mmlu_eval_accuracy_sociology": 0.6363636363636364,
      "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
      "mmlu_eval_accuracy_virology": 0.4444444444444444,
      "mmlu_eval_accuracy_world_religions": 0.6842105263157895,
      "mmlu_loss": 1.064671132450938,
      "step": 800
    },
    {
      "epoch": 1.0,
      "learning_rate": 0.0002,
      "loss": 0.5135,
      "step": 810
    },
    {
      "epoch": 1.01,
      "learning_rate": 0.0002,
      "loss": 0.4532,
      "step": 820
    },
    {
      "epoch": 1.02,
      "learning_rate": 0.0002,
      "loss": 0.4483,
      "step": 830
    },
    {
      "epoch": 1.04,
      "learning_rate": 0.0002,
      "loss": 0.4507,
      "step": 840
    },
    {
      "epoch": 1.05,
      "learning_rate": 0.0002,
      "loss": 0.4572,
      "step": 850
    },
    {
      "epoch": 1.06,
      "learning_rate": 0.0002,
      "loss": 0.4346,
      "step": 860
    },
    {
      "epoch": 1.07,
      "learning_rate": 0.0002,
      "loss": 0.4306,
      "step": 870
    },
    {
      "epoch": 1.09,
      "learning_rate": 0.0002,
      "loss": 0.439,
      "step": 880
    },
    {
      "epoch": 1.1,
      "learning_rate": 0.0002,
      "loss": 0.4215,
      "step": 890
    },
    {
      "epoch": 1.11,
      "learning_rate": 0.0002,
      "loss": 0.4608,
      "step": 900
    },
    {
      "epoch": 1.12,
      "learning_rate": 0.0002,
      "loss": 0.4345,
      "step": 910
    },
    {
      "epoch": 1.13,
      "learning_rate": 0.0002,
      "loss": 0.422,
      "step": 920
    },
    {
      "epoch": 1.15,
      "learning_rate": 0.0002,
      "loss": 0.4444,
      "step": 930
    },
    {
      "epoch": 1.16,
      "learning_rate": 0.0002,
      "loss": 0.4649,
      "step": 940
    },
    {
      "epoch": 1.17,
      "learning_rate": 0.0002,
      "loss": 0.4508,
      "step": 950
    },
    {
      "epoch": 1.18,
      "learning_rate": 0.0002,
      "loss": 0.439,
      "step": 960
    },
    {
      "epoch": 1.2,
      "learning_rate": 0.0002,
      "loss": 0.4347,
      "step": 970
    },
    {
      "epoch": 1.21,
      "learning_rate": 0.0002,
      "loss": 0.4413,
      "step": 980
    },
    {
      "epoch": 1.22,
      "learning_rate": 0.0002,
      "loss": 0.4337,
      "step": 990
    },
    {
      "epoch": 1.23,
      "learning_rate": 0.0002,
      "loss": 0.4358,
      "step": 1000
    },
    {
      "epoch": 1.23,
      "eval_loss": 0.5019292235374451,
      "eval_runtime": 249.7097,
      "eval_samples_per_second": 4.005,
      "eval_steps_per_second": 2.002,
      "step": 1000
    },
    {
      "epoch": 1.23,
      "mmlu_eval_accuracy": 0.46197732544268794,
      "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
      "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
      "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": 0.5,
      "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": 0.36363636363636365,
      "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": 0.3170731707317073,
      "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": 0.3181818181818182,
      "mmlu_eval_accuracy_high_school_computer_science": 0.4444444444444444,
      "mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
      "mmlu_eval_accuracy_high_school_geography": 0.6363636363636364,
      "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": 0.29411764705882354,
      "mmlu_eval_accuracy_high_school_psychology": 0.7333333333333333,
      "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
      "mmlu_eval_accuracy_high_school_us_history": 0.7272727272727273,
      "mmlu_eval_accuracy_high_school_world_history": 0.6153846153846154,
      "mmlu_eval_accuracy_human_aging": 0.6956521739130435,
      "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
      "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": 0.8,
      "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
      "mmlu_eval_accuracy_miscellaneous": 0.6395348837209303,
      "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
      "mmlu_eval_accuracy_moral_scenarios": 0.24,
      "mmlu_eval_accuracy_nutrition": 0.5757575757575758,
      "mmlu_eval_accuracy_philosophy": 0.4117647058823529,
      "mmlu_eval_accuracy_prehistory": 0.5428571428571428,
      "mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
      "mmlu_eval_accuracy_professional_law": 0.32941176470588235,
      "mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
      "mmlu_eval_accuracy_professional_psychology": 0.3188405797101449,
      "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
      "mmlu_eval_accuracy_security_studies": 0.5185185185185185,
      "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": 0.7368421052631579,
      "mmlu_loss": 1.103624303117589,
      "step": 1000
    },
    {
      "epoch": 1.25,
      "learning_rate": 0.0002,
      "loss": 0.4428,
      "step": 1010
    },
    {
      "epoch": 1.26,
      "learning_rate": 0.0002,
      "loss": 0.4306,
      "step": 1020
    },
    {
      "epoch": 1.27,
      "learning_rate": 0.0002,
      "loss": 0.4585,
      "step": 1030
    },
    {
      "epoch": 1.28,
      "learning_rate": 0.0002,
      "loss": 0.4323,
      "step": 1040
    },
    {
      "epoch": 1.29,
      "learning_rate": 0.0002,
      "loss": 0.4333,
      "step": 1050
    },
    {
      "epoch": 1.31,
      "learning_rate": 0.0002,
      "loss": 0.4364,
      "step": 1060
    },
    {
      "epoch": 1.32,
      "learning_rate": 0.0002,
      "loss": 0.4256,
      "step": 1070
    },
    {
      "epoch": 1.33,
      "learning_rate": 0.0002,
      "loss": 0.4197,
      "step": 1080
    },
    {
      "epoch": 1.34,
      "learning_rate": 0.0002,
      "loss": 0.4382,
      "step": 1090
    },
    {
      "epoch": 1.36,
      "learning_rate": 0.0002,
      "loss": 0.4489,
      "step": 1100
    },
    {
      "epoch": 1.37,
      "learning_rate": 0.0002,
      "loss": 0.4152,
      "step": 1110
    },
    {
      "epoch": 1.38,
      "learning_rate": 0.0002,
      "loss": 0.425,
      "step": 1120
    },
    {
      "epoch": 1.39,
      "learning_rate": 0.0002,
      "loss": 0.4537,
      "step": 1130
    },
    {
      "epoch": 1.41,
      "learning_rate": 0.0002,
      "loss": 0.4496,
      "step": 1140
    },
    {
      "epoch": 1.42,
      "learning_rate": 0.0002,
      "loss": 0.4266,
      "step": 1150
    },
    {
      "epoch": 1.43,
      "learning_rate": 0.0002,
      "loss": 0.4449,
      "step": 1160
    },
    {
      "epoch": 1.44,
      "learning_rate": 0.0002,
      "loss": 0.4381,
      "step": 1170
    },
    {
      "epoch": 1.45,
      "learning_rate": 0.0002,
      "loss": 0.4272,
      "step": 1180
    },
    {
      "epoch": 1.47,
      "learning_rate": 0.0002,
      "loss": 0.4366,
      "step": 1190
    },
    {
      "epoch": 1.48,
      "learning_rate": 0.0002,
      "loss": 0.428,
      "step": 1200
    },
    {
      "epoch": 1.48,
      "eval_loss": 0.4976211488246918,
      "eval_runtime": 249.5918,
      "eval_samples_per_second": 4.007,
      "eval_steps_per_second": 2.003,
      "step": 1200
    },
    {
      "epoch": 1.48,
      "mmlu_eval_accuracy": 0.4642275199494228,
      "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
      "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
      "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": 0.5,
      "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": 0.36363636363636365,
      "mmlu_eval_accuracy_college_physics": 0.5454545454545454,
      "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": 0.3170731707317073,
      "mmlu_eval_accuracy_formal_logic": 0.21428571428571427,
      "mmlu_eval_accuracy_global_facts": 0.6,
      "mmlu_eval_accuracy_high_school_biology": 0.375,
      "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
      "mmlu_eval_accuracy_high_school_computer_science": 0.4444444444444444,
      "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_geography": 0.6818181818181818,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.3488372093023256,
      "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156,
      "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
      "mmlu_eval_accuracy_high_school_psychology": 0.7833333333333333,
      "mmlu_eval_accuracy_high_school_statistics": 0.2608695652173913,
      "mmlu_eval_accuracy_high_school_us_history": 0.7272727272727273,
      "mmlu_eval_accuracy_high_school_world_history": 0.6153846153846154,
      "mmlu_eval_accuracy_human_aging": 0.7391304347826086,
      "mmlu_eval_accuracy_human_sexuality": 0.5,
      "mmlu_eval_accuracy_international_law": 0.6923076923076923,
      "mmlu_eval_accuracy_jurisprudence": 0.5454545454545454,
      "mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
      "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
      "mmlu_eval_accuracy_management": 0.6363636363636364,
      "mmlu_eval_accuracy_marketing": 0.76,
      "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
      "mmlu_eval_accuracy_miscellaneous": 0.6395348837209303,
      "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
      "mmlu_eval_accuracy_moral_scenarios": 0.24,
      "mmlu_eval_accuracy_nutrition": 0.48484848484848486,
      "mmlu_eval_accuracy_philosophy": 0.38235294117647056,
      "mmlu_eval_accuracy_prehistory": 0.5428571428571428,
      "mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
      "mmlu_eval_accuracy_professional_law": 0.34705882352941175,
      "mmlu_eval_accuracy_professional_medicine": 0.45161290322580644,
      "mmlu_eval_accuracy_professional_psychology": 0.34782608695652173,
      "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
      "mmlu_eval_accuracy_security_studies": 0.5185185185185185,
      "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": 0.7368421052631579,
      "mmlu_loss": 1.0431902918079503,
      "step": 1200
    },
    {
      "epoch": 1.49,
      "learning_rate": 0.0002,
      "loss": 0.4388,
      "step": 1210
    },
    {
      "epoch": 1.5,
      "learning_rate": 0.0002,
      "loss": 0.4396,
      "step": 1220
    },
    {
      "epoch": 1.52,
      "learning_rate": 0.0002,
      "loss": 0.448,
      "step": 1230
    },
    {
      "epoch": 1.53,
      "learning_rate": 0.0002,
      "loss": 0.4294,
      "step": 1240
    },
    {
      "epoch": 1.54,
      "learning_rate": 0.0002,
      "loss": 0.427,
      "step": 1250
    },
    {
      "epoch": 1.55,
      "learning_rate": 0.0002,
      "loss": 0.4464,
      "step": 1260
    },
    {
      "epoch": 1.57,
      "learning_rate": 0.0002,
      "loss": 0.4319,
      "step": 1270
    },
    {
      "epoch": 1.58,
      "learning_rate": 0.0002,
      "loss": 0.4297,
      "step": 1280
    },
    {
      "epoch": 1.59,
      "learning_rate": 0.0002,
      "loss": 0.4266,
      "step": 1290
    },
    {
      "epoch": 1.6,
      "learning_rate": 0.0002,
      "loss": 0.4567,
      "step": 1300
    },
    {
      "epoch": 1.62,
      "learning_rate": 0.0002,
      "loss": 0.4496,
      "step": 1310
    },
    {
      "epoch": 1.63,
      "learning_rate": 0.0002,
      "loss": 0.4408,
      "step": 1320
    },
    {
      "epoch": 1.64,
      "learning_rate": 0.0002,
      "loss": 0.4487,
      "step": 1330
    },
    {
      "epoch": 1.65,
      "learning_rate": 0.0002,
      "loss": 0.4168,
      "step": 1340
    },
    {
      "epoch": 1.66,
      "learning_rate": 0.0002,
      "loss": 0.4418,
      "step": 1350
    },
    {
      "epoch": 1.68,
      "learning_rate": 0.0002,
      "loss": 0.4288,
      "step": 1360
    },
    {
      "epoch": 1.69,
      "learning_rate": 0.0002,
      "loss": 0.4305,
      "step": 1370
    },
    {
      "epoch": 1.7,
      "learning_rate": 0.0002,
      "loss": 0.425,
      "step": 1380
    },
    {
      "epoch": 1.71,
      "learning_rate": 0.0002,
      "loss": 0.4247,
      "step": 1390
    },
    {
      "epoch": 1.73,
      "learning_rate": 0.0002,
      "loss": 0.4276,
      "step": 1400
    },
    {
      "epoch": 1.73,
      "eval_loss": 0.49078691005706787,
      "eval_runtime": 249.9521,
      "eval_samples_per_second": 4.001,
      "eval_steps_per_second": 2.0,
      "step": 1400
    },
    {
      "epoch": 1.73,
      "mmlu_eval_accuracy": 0.46579887678101295,
      "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
      "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
      "mmlu_eval_accuracy_astronomy": 0.3125,
      "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
      "mmlu_eval_accuracy_clinical_knowledge": 0.41379310344827586,
      "mmlu_eval_accuracy_college_biology": 0.5,
      "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": 0.5454545454545454,
      "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": 0.375,
      "mmlu_eval_accuracy_elementary_mathematics": 0.3170731707317073,
      "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
      "mmlu_eval_accuracy_global_facts": 0.6,
      "mmlu_eval_accuracy_high_school_biology": 0.375,
      "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
      "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
      "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_geography": 0.6818181818181818,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723,
      "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.5,
      "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
      "mmlu_eval_accuracy_high_school_psychology": 0.7833333333333333,
      "mmlu_eval_accuracy_high_school_statistics": 0.2608695652173913,
      "mmlu_eval_accuracy_high_school_us_history": 0.6818181818181818,
      "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": 0.5454545454545454,
      "mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
      "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
      "mmlu_eval_accuracy_management": 0.45454545454545453,
      "mmlu_eval_accuracy_marketing": 0.72,
      "mmlu_eval_accuracy_medical_genetics": 0.6363636363636364,
      "mmlu_eval_accuracy_miscellaneous": 0.6395348837209303,
      "mmlu_eval_accuracy_moral_disputes": 0.5,
      "mmlu_eval_accuracy_moral_scenarios": 0.24,
      "mmlu_eval_accuracy_nutrition": 0.5454545454545454,
      "mmlu_eval_accuracy_philosophy": 0.38235294117647056,
      "mmlu_eval_accuracy_prehistory": 0.5714285714285714,
      "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
      "mmlu_eval_accuracy_professional_law": 0.35294117647058826,
      "mmlu_eval_accuracy_professional_medicine": 0.4838709677419355,
      "mmlu_eval_accuracy_professional_psychology": 0.3188405797101449,
      "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
      "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": 1.1886581055839442,
      "step": 1400
    },
    {
      "epoch": 1.74,
      "learning_rate": 0.0002,
      "loss": 0.4448,
      "step": 1410
    },
    {
      "epoch": 1.75,
      "learning_rate": 0.0002,
      "loss": 0.4305,
      "step": 1420
    },
    {
      "epoch": 1.76,
      "learning_rate": 0.0002,
      "loss": 0.4262,
      "step": 1430
    },
    {
      "epoch": 1.78,
      "learning_rate": 0.0002,
      "loss": 0.4274,
      "step": 1440
    },
    {
      "epoch": 1.79,
      "learning_rate": 0.0002,
      "loss": 0.4375,
      "step": 1450
    },
    {
      "epoch": 1.8,
      "learning_rate": 0.0002,
      "loss": 0.4295,
      "step": 1460
    },
    {
      "epoch": 1.81,
      "learning_rate": 0.0002,
      "loss": 0.439,
      "step": 1470
    },
    {
      "epoch": 1.82,
      "learning_rate": 0.0002,
      "loss": 0.4182,
      "step": 1480
    },
    {
      "epoch": 1.84,
      "learning_rate": 0.0002,
      "loss": 0.4162,
      "step": 1490
    },
    {
      "epoch": 1.85,
      "learning_rate": 0.0002,
      "loss": 0.4348,
      "step": 1500
    },
    {
      "epoch": 1.86,
      "learning_rate": 0.0002,
      "loss": 0.4407,
      "step": 1510
    },
    {
      "epoch": 1.87,
      "learning_rate": 0.0002,
      "loss": 0.4213,
      "step": 1520
    },
    {
      "epoch": 1.89,
      "learning_rate": 0.0002,
      "loss": 0.4188,
      "step": 1530
    },
    {
      "epoch": 1.9,
      "learning_rate": 0.0002,
      "loss": 0.4591,
      "step": 1540
    },
    {
      "epoch": 1.91,
      "learning_rate": 0.0002,
      "loss": 0.4098,
      "step": 1550
    },
    {
      "epoch": 1.92,
      "learning_rate": 0.0002,
      "loss": 0.4331,
      "step": 1560
    },
    {
      "epoch": 1.94,
      "learning_rate": 0.0002,
      "loss": 0.4383,
      "step": 1570
    },
    {
      "epoch": 1.95,
      "learning_rate": 0.0002,
      "loss": 0.4334,
      "step": 1580
    },
    {
      "epoch": 1.96,
      "learning_rate": 0.0002,
      "loss": 0.4363,
      "step": 1590
    },
    {
      "epoch": 1.97,
      "learning_rate": 0.0002,
      "loss": 0.4227,
      "step": 1600
    },
    {
      "epoch": 1.97,
      "eval_loss": 0.48671162128448486,
      "eval_runtime": 249.6163,
      "eval_samples_per_second": 4.006,
      "eval_steps_per_second": 2.003,
      "step": 1600
    },
    {
      "epoch": 1.97,
      "mmlu_eval_accuracy": 0.4663407571795711,
      "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
      "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
      "mmlu_eval_accuracy_astronomy": 0.4375,
      "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
      "mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655,
      "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": 0.2727272727272727,
      "mmlu_eval_accuracy_college_medicine": 0.3181818181818182,
      "mmlu_eval_accuracy_college_physics": 0.5454545454545454,
      "mmlu_eval_accuracy_computer_security": 0.6363636363636364,
      "mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
      "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": 0.21428571428571427,
      "mmlu_eval_accuracy_global_facts": 0.5,
      "mmlu_eval_accuracy_high_school_biology": 0.375,
      "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
      "mmlu_eval_accuracy_high_school_computer_science": 0.4444444444444444,
      "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": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.37209302325581395,
      "mmlu_eval_accuracy_high_school_mathematics": 0.1724137931034483,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156,
      "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": 0.5769230769230769,
      "mmlu_eval_accuracy_human_aging": 0.6956521739130435,
      "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
      "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": 0.2727272727272727,
      "mmlu_eval_accuracy_management": 0.7272727272727273,
      "mmlu_eval_accuracy_marketing": 0.76,
      "mmlu_eval_accuracy_medical_genetics": 0.6363636363636364,
      "mmlu_eval_accuracy_miscellaneous": 0.6511627906976745,
      "mmlu_eval_accuracy_moral_disputes": 0.5263157894736842,
      "mmlu_eval_accuracy_moral_scenarios": 0.23,
      "mmlu_eval_accuracy_nutrition": 0.48484848484848486,
      "mmlu_eval_accuracy_philosophy": 0.3235294117647059,
      "mmlu_eval_accuracy_prehistory": 0.5428571428571428,
      "mmlu_eval_accuracy_professional_accounting": 0.3225806451612903,
      "mmlu_eval_accuracy_professional_law": 0.32941176470588235,
      "mmlu_eval_accuracy_professional_medicine": 0.45161290322580644,
      "mmlu_eval_accuracy_professional_psychology": 0.30434782608695654,
      "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
      "mmlu_eval_accuracy_security_studies": 0.5185185185185185,
      "mmlu_eval_accuracy_sociology": 0.5909090909090909,
      "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
      "mmlu_eval_accuracy_virology": 0.3888888888888889,
      "mmlu_eval_accuracy_world_religions": 0.6842105263157895,
      "mmlu_loss": 1.050787725118682,
      "step": 1600
    },
    {
      "epoch": 1.99,
      "learning_rate": 0.0002,
      "loss": 0.4297,
      "step": 1610
    },
    {
      "epoch": 2.0,
      "learning_rate": 0.0002,
      "loss": 0.4376,
      "step": 1620
    },
    {
      "epoch": 2.01,
      "learning_rate": 0.0002,
      "loss": 0.3567,
      "step": 1630
    },
    {
      "epoch": 2.02,
      "learning_rate": 0.0002,
      "loss": 0.332,
      "step": 1640
    },
    {
      "epoch": 2.03,
      "learning_rate": 0.0002,
      "loss": 0.3284,
      "step": 1650
    },
    {
      "epoch": 2.05,
      "learning_rate": 0.0002,
      "loss": 0.3347,
      "step": 1660
    },
    {
      "epoch": 2.06,
      "learning_rate": 0.0002,
      "loss": 0.3498,
      "step": 1670
    },
    {
      "epoch": 2.07,
      "learning_rate": 0.0002,
      "loss": 0.3541,
      "step": 1680
    },
    {
      "epoch": 2.08,
      "learning_rate": 0.0002,
      "loss": 0.34,
      "step": 1690
    },
    {
      "epoch": 2.1,
      "learning_rate": 0.0002,
      "loss": 0.3507,
      "step": 1700
    },
    {
      "epoch": 2.11,
      "learning_rate": 0.0002,
      "loss": 0.3518,
      "step": 1710
    },
    {
      "epoch": 2.12,
      "learning_rate": 0.0002,
      "loss": 0.3515,
      "step": 1720
    },
    {
      "epoch": 2.13,
      "learning_rate": 0.0002,
      "loss": 0.3432,
      "step": 1730
    },
    {
      "epoch": 2.15,
      "learning_rate": 0.0002,
      "loss": 0.355,
      "step": 1740
    },
    {
      "epoch": 2.16,
      "learning_rate": 0.0002,
      "loss": 0.3463,
      "step": 1750
    },
    {
      "epoch": 2.17,
      "learning_rate": 0.0002,
      "loss": 0.337,
      "step": 1760
    },
    {
      "epoch": 2.18,
      "learning_rate": 0.0002,
      "loss": 0.3524,
      "step": 1770
    },
    {
      "epoch": 2.19,
      "learning_rate": 0.0002,
      "loss": 0.3414,
      "step": 1780
    },
    {
      "epoch": 2.21,
      "learning_rate": 0.0002,
      "loss": 0.3505,
      "step": 1790
    },
    {
      "epoch": 2.22,
      "learning_rate": 0.0002,
      "loss": 0.3371,
      "step": 1800
    },
    {
      "epoch": 2.22,
      "eval_loss": 0.5045116543769836,
      "eval_runtime": 249.7171,
      "eval_samples_per_second": 4.005,
      "eval_steps_per_second": 2.002,
      "step": 1800
    },
    {
      "epoch": 2.22,
      "mmlu_eval_accuracy": 0.4648096685434819,
      "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
      "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
      "mmlu_eval_accuracy_astronomy": 0.375,
      "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
      "mmlu_eval_accuracy_clinical_knowledge": 0.41379310344827586,
      "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": 0.2727272727272727,
      "mmlu_eval_accuracy_college_physics": 0.5454545454545454,
      "mmlu_eval_accuracy_computer_security": 0.5454545454545454,
      "mmlu_eval_accuracy_conceptual_physics": 0.46153846153846156,
      "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
      "mmlu_eval_accuracy_electrical_engineering": 0.4375,
      "mmlu_eval_accuracy_elementary_mathematics": 0.3902439024390244,
      "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
      "mmlu_eval_accuracy_global_facts": 0.6,
      "mmlu_eval_accuracy_high_school_biology": 0.40625,
      "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
      "mmlu_eval_accuracy_high_school_computer_science": 0.4444444444444444,
      "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": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.37209302325581395,
      "mmlu_eval_accuracy_high_school_mathematics": 0.1724137931034483,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.5,
      "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
      "mmlu_eval_accuracy_high_school_psychology": 0.75,
      "mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
      "mmlu_eval_accuracy_high_school_us_history": 0.8181818181818182,
      "mmlu_eval_accuracy_high_school_world_history": 0.5769230769230769,
      "mmlu_eval_accuracy_human_aging": 0.7391304347826086,
      "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
      "mmlu_eval_accuracy_international_law": 0.6923076923076923,
      "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
      "mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
      "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
      "mmlu_eval_accuracy_management": 0.5454545454545454,
      "mmlu_eval_accuracy_marketing": 0.68,
      "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
      "mmlu_eval_accuracy_miscellaneous": 0.6511627906976745,
      "mmlu_eval_accuracy_moral_disputes": 0.5263157894736842,
      "mmlu_eval_accuracy_moral_scenarios": 0.23,
      "mmlu_eval_accuracy_nutrition": 0.5151515151515151,
      "mmlu_eval_accuracy_philosophy": 0.4117647058823529,
      "mmlu_eval_accuracy_prehistory": 0.5142857142857142,
      "mmlu_eval_accuracy_professional_accounting": 0.22580645161290322,
      "mmlu_eval_accuracy_professional_law": 0.3588235294117647,
      "mmlu_eval_accuracy_professional_medicine": 0.45161290322580644,
      "mmlu_eval_accuracy_professional_psychology": 0.3333333333333333,
      "mmlu_eval_accuracy_public_relations": 0.3333333333333333,
      "mmlu_eval_accuracy_security_studies": 0.5185185185185185,
      "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": 1.1527424410141167,
      "step": 1800
    },
    {
      "epoch": 2.23,
      "learning_rate": 0.0002,
      "loss": 0.334,
      "step": 1810
    },
    {
      "epoch": 2.24,
      "learning_rate": 0.0002,
      "loss": 0.3392,
      "step": 1820
    },
    {
      "epoch": 2.26,
      "learning_rate": 0.0002,
      "loss": 0.3377,
      "step": 1830
    },
    {
      "epoch": 2.27,
      "learning_rate": 0.0002,
      "loss": 0.3432,
      "step": 1840
    },
    {
      "epoch": 2.28,
      "learning_rate": 0.0002,
      "loss": 0.3581,
      "step": 1850
    },
    {
      "epoch": 2.29,
      "learning_rate": 0.0002,
      "loss": 0.3423,
      "step": 1860
    },
    {
      "epoch": 2.31,
      "learning_rate": 0.0002,
      "loss": 0.346,
      "step": 1870
    },
    {
      "epoch": 2.32,
      "learning_rate": 0.0002,
      "loss": 0.3361,
      "step": 1880
    },
    {
      "epoch": 2.33,
      "learning_rate": 0.0002,
      "loss": 0.3508,
      "step": 1890
    },
    {
      "epoch": 2.34,
      "learning_rate": 0.0002,
      "loss": 0.3502,
      "step": 1900
    },
    {
      "epoch": 2.36,
      "learning_rate": 0.0002,
      "loss": 0.3331,
      "step": 1910
    },
    {
      "epoch": 2.37,
      "learning_rate": 0.0002,
      "loss": 0.3504,
      "step": 1920
    },
    {
      "epoch": 2.38,
      "learning_rate": 0.0002,
      "loss": 0.3589,
      "step": 1930
    },
    {
      "epoch": 2.39,
      "learning_rate": 0.0002,
      "loss": 0.3477,
      "step": 1940
    },
    {
      "epoch": 2.4,
      "learning_rate": 0.0002,
      "loss": 0.3519,
      "step": 1950
    },
    {
      "epoch": 2.42,
      "learning_rate": 0.0002,
      "loss": 0.3549,
      "step": 1960
    },
    {
      "epoch": 2.43,
      "learning_rate": 0.0002,
      "loss": 0.3662,
      "step": 1970
    },
    {
      "epoch": 2.44,
      "learning_rate": 0.0002,
      "loss": 0.3611,
      "step": 1980
    },
    {
      "epoch": 2.45,
      "learning_rate": 0.0002,
      "loss": 0.3506,
      "step": 1990
    },
    {
      "epoch": 2.47,
      "learning_rate": 0.0002,
      "loss": 0.3577,
      "step": 2000
    },
    {
      "epoch": 2.47,
      "eval_loss": 0.5058008432388306,
      "eval_runtime": 249.914,
      "eval_samples_per_second": 4.001,
      "eval_steps_per_second": 2.001,
      "step": 2000
    },
    {
      "epoch": 2.47,
      "mmlu_eval_accuracy": 0.46507901610100333,
      "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
      "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": 0.125,
      "mmlu_eval_accuracy_college_computer_science": 0.45454545454545453,
      "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
      "mmlu_eval_accuracy_college_medicine": 0.36363636363636365,
      "mmlu_eval_accuracy_college_physics": 0.5454545454545454,
      "mmlu_eval_accuracy_computer_security": 0.5454545454545454,
      "mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
      "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
      "mmlu_eval_accuracy_electrical_engineering": 0.375,
      "mmlu_eval_accuracy_elementary_mathematics": 0.36585365853658536,
      "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
      "mmlu_eval_accuracy_global_facts": 0.5,
      "mmlu_eval_accuracy_high_school_biology": 0.40625,
      "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
      "mmlu_eval_accuracy_high_school_computer_science": 0.4444444444444444,
      "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_geography": 0.6818181818181818,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.3953488372093023,
      "mmlu_eval_accuracy_high_school_mathematics": 0.1724137931034483,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156,
      "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
      "mmlu_eval_accuracy_high_school_psychology": 0.7,
      "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
      "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
      "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": 0.7692307692307693,
      "mmlu_eval_accuracy_jurisprudence": 0.5454545454545454,
      "mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
      "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
      "mmlu_eval_accuracy_management": 0.6363636363636364,
      "mmlu_eval_accuracy_marketing": 0.68,
      "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
      "mmlu_eval_accuracy_miscellaneous": 0.6395348837209303,
      "mmlu_eval_accuracy_moral_disputes": 0.5,
      "mmlu_eval_accuracy_moral_scenarios": 0.24,
      "mmlu_eval_accuracy_nutrition": 0.5151515151515151,
      "mmlu_eval_accuracy_philosophy": 0.35294117647058826,
      "mmlu_eval_accuracy_prehistory": 0.5142857142857142,
      "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
      "mmlu_eval_accuracy_professional_law": 0.32941176470588235,
      "mmlu_eval_accuracy_professional_medicine": 0.4838709677419355,
      "mmlu_eval_accuracy_professional_psychology": 0.3333333333333333,
      "mmlu_eval_accuracy_public_relations": 0.3333333333333333,
      "mmlu_eval_accuracy_security_studies": 0.5185185185185185,
      "mmlu_eval_accuracy_sociology": 0.6363636363636364,
      "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
      "mmlu_eval_accuracy_virology": 0.5555555555555556,
      "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
      "mmlu_loss": 1.1673369506087066,
      "step": 2000
    },
    {
      "epoch": 2.48,
      "learning_rate": 0.0002,
      "loss": 0.3389,
      "step": 2010
    },
    {
      "epoch": 2.49,
      "learning_rate": 0.0002,
      "loss": 0.3547,
      "step": 2020
    },
    {
      "epoch": 2.5,
      "learning_rate": 0.0002,
      "loss": 0.3581,
      "step": 2030
    },
    {
      "epoch": 2.52,
      "learning_rate": 0.0002,
      "loss": 0.3515,
      "step": 2040
    },
    {
      "epoch": 2.53,
      "learning_rate": 0.0002,
      "loss": 0.3472,
      "step": 2050
    },
    {
      "epoch": 2.54,
      "learning_rate": 0.0002,
      "loss": 0.3582,
      "step": 2060
    },
    {
      "epoch": 2.55,
      "learning_rate": 0.0002,
      "loss": 0.3526,
      "step": 2070
    },
    {
      "epoch": 2.56,
      "learning_rate": 0.0002,
      "loss": 0.3662,
      "step": 2080
    },
    {
      "epoch": 2.58,
      "learning_rate": 0.0002,
      "loss": 0.3447,
      "step": 2090
    },
    {
      "epoch": 2.59,
      "learning_rate": 0.0002,
      "loss": 0.3509,
      "step": 2100
    },
    {
      "epoch": 2.6,
      "learning_rate": 0.0002,
      "loss": 0.3501,
      "step": 2110
    },
    {
      "epoch": 2.61,
      "learning_rate": 0.0002,
      "loss": 0.3417,
      "step": 2120
    },
    {
      "epoch": 2.63,
      "learning_rate": 0.0002,
      "loss": 0.34,
      "step": 2130
    },
    {
      "epoch": 2.64,
      "learning_rate": 0.0002,
      "loss": 0.3572,
      "step": 2140
    },
    {
      "epoch": 2.65,
      "learning_rate": 0.0002,
      "loss": 0.3564,
      "step": 2150
    },
    {
      "epoch": 2.66,
      "learning_rate": 0.0002,
      "loss": 0.347,
      "step": 2160
    },
    {
      "epoch": 2.68,
      "learning_rate": 0.0002,
      "loss": 0.358,
      "step": 2170
    },
    {
      "epoch": 2.69,
      "learning_rate": 0.0002,
      "loss": 0.3448,
      "step": 2180
    },
    {
      "epoch": 2.7,
      "learning_rate": 0.0002,
      "loss": 0.3528,
      "step": 2190
    },
    {
      "epoch": 2.71,
      "learning_rate": 0.0002,
      "loss": 0.3399,
      "step": 2200
    },
    {
      "epoch": 2.71,
      "eval_loss": 0.49899813532829285,
      "eval_runtime": 250.308,
      "eval_samples_per_second": 3.995,
      "eval_steps_per_second": 1.998,
      "step": 2200
    },
    {
      "epoch": 2.71,
      "mmlu_eval_accuracy": 0.4604361808337048,
      "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
      "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
      "mmlu_eval_accuracy_astronomy": 0.4375,
      "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
      "mmlu_eval_accuracy_clinical_knowledge": 0.3793103448275862,
      "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": 0.5454545454545454,
      "mmlu_eval_accuracy_computer_security": 0.6363636363636364,
      "mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
      "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
      "mmlu_eval_accuracy_electrical_engineering": 0.4375,
      "mmlu_eval_accuracy_elementary_mathematics": 0.43902439024390244,
      "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
      "mmlu_eval_accuracy_global_facts": 0.4,
      "mmlu_eval_accuracy_high_school_biology": 0.40625,
      "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
      "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
      "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
      "mmlu_eval_accuracy_high_school_geography": 0.6818181818181818,
      "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714,
      "mmlu_eval_accuracy_high_school_macroeconomics": 0.3488372093023256,
      "mmlu_eval_accuracy_high_school_mathematics": 0.13793103448275862,
      "mmlu_eval_accuracy_high_school_microeconomics": 0.5769230769230769,
      "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
      "mmlu_eval_accuracy_high_school_psychology": 0.75,
      "mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
      "mmlu_eval_accuracy_high_school_us_history": 0.7727272727272727,
      "mmlu_eval_accuracy_high_school_world_history": 0.5384615384615384,
      "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
      "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
      "mmlu_eval_accuracy_international_law": 0.6923076923076923,
      "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
      "mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
      "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
      "mmlu_eval_accuracy_management": 0.5454545454545454,
      "mmlu_eval_accuracy_marketing": 0.68,
      "mmlu_eval_accuracy_medical_genetics": 0.6363636363636364,
      "mmlu_eval_accuracy_miscellaneous": 0.6511627906976745,
      "mmlu_eval_accuracy_moral_disputes": 0.5263157894736842,
      "mmlu_eval_accuracy_moral_scenarios": 0.24,
      "mmlu_eval_accuracy_nutrition": 0.45454545454545453,
      "mmlu_eval_accuracy_philosophy": 0.38235294117647056,
      "mmlu_eval_accuracy_prehistory": 0.5428571428571428,
      "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
      "mmlu_eval_accuracy_professional_law": 0.35294117647058826,
      "mmlu_eval_accuracy_professional_medicine": 0.4838709677419355,
      "mmlu_eval_accuracy_professional_psychology": 0.3188405797101449,
      "mmlu_eval_accuracy_public_relations": 0.3333333333333333,
      "mmlu_eval_accuracy_security_studies": 0.5185185185185185,
      "mmlu_eval_accuracy_sociology": 0.6363636363636364,
      "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
      "mmlu_eval_accuracy_virology": 0.3888888888888889,
      "mmlu_eval_accuracy_world_religions": 0.6842105263157895,
      "mmlu_loss": 0.9543326205425645,
      "step": 2200
    }
  ],
  "max_steps": 5000,
  "num_train_epochs": 7,
  "total_flos": 5.97973549929726e+17,
  "trial_name": null,
  "trial_params": null
}