Farouk
commit files to HF hub
9df6733
{
"best_metric": 0.7639025449752808,
"best_model_checkpoint": "./output_v2/7b_cluster022_Nous-Hermes-llama-2-7b_partitioned_v3_standardized_022/checkpoint-2800",
"epoch": 1.199400299850075,
"global_step": 3400,
"is_hyper_param_search": false,
"is_local_process_zero": true,
"is_world_process_zero": true,
"log_history": [
{
"epoch": 0.0,
"learning_rate": 0.0002,
"loss": 0.8325,
"step": 10
},
{
"epoch": 0.01,
"learning_rate": 0.0002,
"loss": 0.8202,
"step": 20
},
{
"epoch": 0.01,
"learning_rate": 0.0002,
"loss": 0.7466,
"step": 30
},
{
"epoch": 0.01,
"learning_rate": 0.0002,
"loss": 0.7549,
"step": 40
},
{
"epoch": 0.02,
"learning_rate": 0.0002,
"loss": 0.7569,
"step": 50
},
{
"epoch": 0.02,
"learning_rate": 0.0002,
"loss": 0.7691,
"step": 60
},
{
"epoch": 0.02,
"learning_rate": 0.0002,
"loss": 0.744,
"step": 70
},
{
"epoch": 0.03,
"learning_rate": 0.0002,
"loss": 0.7708,
"step": 80
},
{
"epoch": 0.03,
"learning_rate": 0.0002,
"loss": 0.8071,
"step": 90
},
{
"epoch": 0.04,
"learning_rate": 0.0002,
"loss": 0.7303,
"step": 100
},
{
"epoch": 0.04,
"learning_rate": 0.0002,
"loss": 0.6861,
"step": 110
},
{
"epoch": 0.04,
"learning_rate": 0.0002,
"loss": 0.7592,
"step": 120
},
{
"epoch": 0.05,
"learning_rate": 0.0002,
"loss": 0.7361,
"step": 130
},
{
"epoch": 0.05,
"learning_rate": 0.0002,
"loss": 0.76,
"step": 140
},
{
"epoch": 0.05,
"learning_rate": 0.0002,
"loss": 0.7617,
"step": 150
},
{
"epoch": 0.06,
"learning_rate": 0.0002,
"loss": 0.7073,
"step": 160
},
{
"epoch": 0.06,
"learning_rate": 0.0002,
"loss": 0.7581,
"step": 170
},
{
"epoch": 0.06,
"learning_rate": 0.0002,
"loss": 0.7636,
"step": 180
},
{
"epoch": 0.07,
"learning_rate": 0.0002,
"loss": 0.7712,
"step": 190
},
{
"epoch": 0.07,
"learning_rate": 0.0002,
"loss": 0.7547,
"step": 200
},
{
"epoch": 0.07,
"eval_loss": 0.8007758259773254,
"eval_runtime": 185.4331,
"eval_samples_per_second": 5.393,
"eval_steps_per_second": 2.696,
"step": 200
},
{
"epoch": 0.07,
"mmlu_eval_accuracy": 0.4659766842502547,
"mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
"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": 0.45454545454545453,
"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": 0.34615384615384615,
"mmlu_eval_accuracy_econometrics": 0.16666666666666666,
"mmlu_eval_accuracy_electrical_engineering": 0.3125,
"mmlu_eval_accuracy_elementary_mathematics": 0.2682926829268293,
"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": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
"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": 0.2413793103448276,
"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": 0.34782608695652173,
"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": 0.7692307692307693,
"mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
"mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
"mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
"mmlu_eval_accuracy_management": 0.7272727272727273,
"mmlu_eval_accuracy_marketing": 0.72,
"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": 0.24,
"mmlu_eval_accuracy_nutrition": 0.5757575757575758,
"mmlu_eval_accuracy_philosophy": 0.5,
"mmlu_eval_accuracy_prehistory": 0.5142857142857142,
"mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
"mmlu_eval_accuracy_professional_law": 0.3411764705882353,
"mmlu_eval_accuracy_professional_medicine": 0.45161290322580644,
"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": 0.3888888888888889,
"mmlu_eval_accuracy_world_religions": 0.7368421052631579,
"mmlu_loss": 1.0009409290575484,
"step": 200
},
{
"epoch": 0.07,
"learning_rate": 0.0002,
"loss": 0.7814,
"step": 210
},
{
"epoch": 0.08,
"learning_rate": 0.0002,
"loss": 0.7313,
"step": 220
},
{
"epoch": 0.08,
"learning_rate": 0.0002,
"loss": 0.7217,
"step": 230
},
{
"epoch": 0.08,
"learning_rate": 0.0002,
"loss": 0.7299,
"step": 240
},
{
"epoch": 0.09,
"learning_rate": 0.0002,
"loss": 0.7229,
"step": 250
},
{
"epoch": 0.09,
"learning_rate": 0.0002,
"loss": 0.7271,
"step": 260
},
{
"epoch": 0.1,
"learning_rate": 0.0002,
"loss": 0.7253,
"step": 270
},
{
"epoch": 0.1,
"learning_rate": 0.0002,
"loss": 0.7371,
"step": 280
},
{
"epoch": 0.1,
"learning_rate": 0.0002,
"loss": 0.7434,
"step": 290
},
{
"epoch": 0.11,
"learning_rate": 0.0002,
"loss": 0.6741,
"step": 300
},
{
"epoch": 0.11,
"learning_rate": 0.0002,
"loss": 0.7386,
"step": 310
},
{
"epoch": 0.11,
"learning_rate": 0.0002,
"loss": 0.7441,
"step": 320
},
{
"epoch": 0.12,
"learning_rate": 0.0002,
"loss": 0.7243,
"step": 330
},
{
"epoch": 0.12,
"learning_rate": 0.0002,
"loss": 0.7534,
"step": 340
},
{
"epoch": 0.12,
"learning_rate": 0.0002,
"loss": 0.7187,
"step": 350
},
{
"epoch": 0.13,
"learning_rate": 0.0002,
"loss": 0.7508,
"step": 360
},
{
"epoch": 0.13,
"learning_rate": 0.0002,
"loss": 0.7597,
"step": 370
},
{
"epoch": 0.13,
"learning_rate": 0.0002,
"loss": 0.7398,
"step": 380
},
{
"epoch": 0.14,
"learning_rate": 0.0002,
"loss": 0.6924,
"step": 390
},
{
"epoch": 0.14,
"learning_rate": 0.0002,
"loss": 0.7035,
"step": 400
},
{
"epoch": 0.14,
"eval_loss": 0.7900036573410034,
"eval_runtime": 188.9686,
"eval_samples_per_second": 5.292,
"eval_steps_per_second": 2.646,
"step": 400
},
{
"epoch": 0.14,
"mmlu_eval_accuracy": 0.45327850420813054,
"mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
"mmlu_eval_accuracy_anatomy": 0.5714285714285714,
"mmlu_eval_accuracy_astronomy": 0.5625,
"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": 0.0,
"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": 0.45454545454545453,
"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": 0.3125,
"mmlu_eval_accuracy_elementary_mathematics": 0.36585365853658536,
"mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
"mmlu_eval_accuracy_global_facts": 0.4,
"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": 0.5555555555555556,
"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": 0.20689655172413793,
"mmlu_eval_accuracy_high_school_microeconomics": 0.38461538461538464,
"mmlu_eval_accuracy_high_school_physics": 0.35294117647058826,
"mmlu_eval_accuracy_high_school_psychology": 0.7166666666666667,
"mmlu_eval_accuracy_high_school_statistics": 0.2608695652173913,
"mmlu_eval_accuracy_high_school_us_history": 0.7272727272727273,
"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": 0.6923076923076923,
"mmlu_eval_accuracy_jurisprudence": 0.2727272727272727,
"mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
"mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
"mmlu_eval_accuracy_management": 0.45454545454545453,
"mmlu_eval_accuracy_marketing": 0.76,
"mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
"mmlu_eval_accuracy_miscellaneous": 0.686046511627907,
"mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
"mmlu_eval_accuracy_moral_scenarios": 0.24,
"mmlu_eval_accuracy_nutrition": 0.5454545454545454,
"mmlu_eval_accuracy_philosophy": 0.5,
"mmlu_eval_accuracy_prehistory": 0.5142857142857142,
"mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
"mmlu_eval_accuracy_professional_law": 0.35294117647058826,
"mmlu_eval_accuracy_professional_medicine": 0.3870967741935484,
"mmlu_eval_accuracy_professional_psychology": 0.4057971014492754,
"mmlu_eval_accuracy_public_relations": 0.6666666666666666,
"mmlu_eval_accuracy_security_studies": 0.5185185185185185,
"mmlu_eval_accuracy_sociology": 0.6818181818181818,
"mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
"mmlu_eval_accuracy_virology": 0.4444444444444444,
"mmlu_eval_accuracy_world_religions": 0.7368421052631579,
"mmlu_loss": 1.0370562722026213,
"step": 400
},
{
"epoch": 0.14,
"learning_rate": 0.0002,
"loss": 0.7245,
"step": 410
},
{
"epoch": 0.15,
"learning_rate": 0.0002,
"loss": 0.8027,
"step": 420
},
{
"epoch": 0.15,
"learning_rate": 0.0002,
"loss": 0.7174,
"step": 430
},
{
"epoch": 0.16,
"learning_rate": 0.0002,
"loss": 0.7471,
"step": 440
},
{
"epoch": 0.16,
"learning_rate": 0.0002,
"loss": 0.7263,
"step": 450
},
{
"epoch": 0.16,
"learning_rate": 0.0002,
"loss": 0.7001,
"step": 460
},
{
"epoch": 0.17,
"learning_rate": 0.0002,
"loss": 0.7767,
"step": 470
},
{
"epoch": 0.17,
"learning_rate": 0.0002,
"loss": 0.7406,
"step": 480
},
{
"epoch": 0.17,
"learning_rate": 0.0002,
"loss": 0.7371,
"step": 490
},
{
"epoch": 0.18,
"learning_rate": 0.0002,
"loss": 0.7152,
"step": 500
},
{
"epoch": 0.18,
"learning_rate": 0.0002,
"loss": 0.746,
"step": 510
},
{
"epoch": 0.18,
"learning_rate": 0.0002,
"loss": 0.7178,
"step": 520
},
{
"epoch": 0.19,
"learning_rate": 0.0002,
"loss": 0.7056,
"step": 530
},
{
"epoch": 0.19,
"learning_rate": 0.0002,
"loss": 0.6961,
"step": 540
},
{
"epoch": 0.19,
"learning_rate": 0.0002,
"loss": 0.673,
"step": 550
},
{
"epoch": 0.2,
"learning_rate": 0.0002,
"loss": 0.7508,
"step": 560
},
{
"epoch": 0.2,
"learning_rate": 0.0002,
"loss": 0.7508,
"step": 570
},
{
"epoch": 0.2,
"learning_rate": 0.0002,
"loss": 0.7122,
"step": 580
},
{
"epoch": 0.21,
"learning_rate": 0.0002,
"loss": 0.7154,
"step": 590
},
{
"epoch": 0.21,
"learning_rate": 0.0002,
"loss": 0.7587,
"step": 600
},
{
"epoch": 0.21,
"eval_loss": 0.785829484462738,
"eval_runtime": 189.436,
"eval_samples_per_second": 5.279,
"eval_steps_per_second": 2.639,
"step": 600
},
{
"epoch": 0.21,
"mmlu_eval_accuracy": 0.4748863496985387,
"mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
"mmlu_eval_accuracy_anatomy": 0.5714285714285714,
"mmlu_eval_accuracy_astronomy": 0.5625,
"mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
"mmlu_eval_accuracy_clinical_knowledge": 0.41379310344827586,
"mmlu_eval_accuracy_college_biology": 0.375,
"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": 0.45454545454545453,
"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": 0.34146341463414637,
"mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
"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": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
"mmlu_eval_accuracy_high_school_geography": 0.7272727272727273,
"mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
"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": 0.7166666666666667,
"mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
"mmlu_eval_accuracy_high_school_us_history": 0.7272727272727273,
"mmlu_eval_accuracy_high_school_world_history": 0.5,
"mmlu_eval_accuracy_human_aging": 0.7391304347826086,
"mmlu_eval_accuracy_human_sexuality": 0.5,
"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": 0.6363636363636364,
"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": 0.5454545454545454,
"mmlu_eval_accuracy_philosophy": 0.47058823529411764,
"mmlu_eval_accuracy_prehistory": 0.45714285714285713,
"mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
"mmlu_eval_accuracy_professional_law": 0.3411764705882353,
"mmlu_eval_accuracy_professional_medicine": 0.3225806451612903,
"mmlu_eval_accuracy_professional_psychology": 0.42028985507246375,
"mmlu_eval_accuracy_public_relations": 0.5833333333333334,
"mmlu_eval_accuracy_security_studies": 0.5925925925925926,
"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": 0.7894736842105263,
"mmlu_loss": 0.9638749470559798,
"step": 600
},
{
"epoch": 0.22,
"learning_rate": 0.0002,
"loss": 0.8107,
"step": 610
},
{
"epoch": 0.22,
"learning_rate": 0.0002,
"loss": 0.7193,
"step": 620
},
{
"epoch": 0.22,
"learning_rate": 0.0002,
"loss": 0.7275,
"step": 630
},
{
"epoch": 0.23,
"learning_rate": 0.0002,
"loss": 0.7553,
"step": 640
},
{
"epoch": 0.23,
"learning_rate": 0.0002,
"loss": 0.7385,
"step": 650
},
{
"epoch": 0.23,
"learning_rate": 0.0002,
"loss": 0.7071,
"step": 660
},
{
"epoch": 0.24,
"learning_rate": 0.0002,
"loss": 0.7395,
"step": 670
},
{
"epoch": 0.24,
"learning_rate": 0.0002,
"loss": 0.7512,
"step": 680
},
{
"epoch": 0.24,
"learning_rate": 0.0002,
"loss": 0.7063,
"step": 690
},
{
"epoch": 0.25,
"learning_rate": 0.0002,
"loss": 0.723,
"step": 700
},
{
"epoch": 0.25,
"learning_rate": 0.0002,
"loss": 0.7068,
"step": 710
},
{
"epoch": 0.25,
"learning_rate": 0.0002,
"loss": 0.7211,
"step": 720
},
{
"epoch": 0.26,
"learning_rate": 0.0002,
"loss": 0.7123,
"step": 730
},
{
"epoch": 0.26,
"learning_rate": 0.0002,
"loss": 0.6394,
"step": 740
},
{
"epoch": 0.26,
"learning_rate": 0.0002,
"loss": 0.679,
"step": 750
},
{
"epoch": 0.27,
"learning_rate": 0.0002,
"loss": 0.7402,
"step": 760
},
{
"epoch": 0.27,
"learning_rate": 0.0002,
"loss": 0.7634,
"step": 770
},
{
"epoch": 0.28,
"learning_rate": 0.0002,
"loss": 0.7253,
"step": 780
},
{
"epoch": 0.28,
"learning_rate": 0.0002,
"loss": 0.7497,
"step": 790
},
{
"epoch": 0.28,
"learning_rate": 0.0002,
"loss": 0.7008,
"step": 800
},
{
"epoch": 0.28,
"eval_loss": 0.7810184359550476,
"eval_runtime": 187.2684,
"eval_samples_per_second": 5.34,
"eval_steps_per_second": 2.67,
"step": 800
},
{
"epoch": 0.28,
"mmlu_eval_accuracy": 0.46145585660156935,
"mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
"mmlu_eval_accuracy_anatomy": 0.5714285714285714,
"mmlu_eval_accuracy_astronomy": 0.4375,
"mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
"mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655,
"mmlu_eval_accuracy_college_biology": 0.4375,
"mmlu_eval_accuracy_college_chemistry": 0.125,
"mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
"mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
"mmlu_eval_accuracy_college_medicine": 0.3181818181818182,
"mmlu_eval_accuracy_college_physics": 0.45454545454545453,
"mmlu_eval_accuracy_computer_security": 0.2727272727272727,
"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": 0.2857142857142857,
"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": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_geography": 0.7272727272727273,
"mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_macroeconomics": 0.3023255813953488,
"mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
"mmlu_eval_accuracy_high_school_microeconomics": 0.4230769230769231,
"mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
"mmlu_eval_accuracy_high_school_psychology": 0.7,
"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": 0.3333333333333333,
"mmlu_eval_accuracy_international_law": 0.7692307692307693,
"mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
"mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
"mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
"mmlu_eval_accuracy_management": 0.5454545454545454,
"mmlu_eval_accuracy_marketing": 0.72,
"mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
"mmlu_eval_accuracy_miscellaneous": 0.6511627906976745,
"mmlu_eval_accuracy_moral_disputes": 0.5,
"mmlu_eval_accuracy_moral_scenarios": 0.23,
"mmlu_eval_accuracy_nutrition": 0.5454545454545454,
"mmlu_eval_accuracy_philosophy": 0.47058823529411764,
"mmlu_eval_accuracy_prehistory": 0.5142857142857142,
"mmlu_eval_accuracy_professional_accounting": 0.3548387096774194,
"mmlu_eval_accuracy_professional_law": 0.3352941176470588,
"mmlu_eval_accuracy_professional_medicine": 0.3870967741935484,
"mmlu_eval_accuracy_professional_psychology": 0.42028985507246375,
"mmlu_eval_accuracy_public_relations": 0.5833333333333334,
"mmlu_eval_accuracy_security_studies": 0.48148148148148145,
"mmlu_eval_accuracy_sociology": 0.6818181818181818,
"mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
"mmlu_eval_accuracy_virology": 0.4444444444444444,
"mmlu_eval_accuracy_world_religions": 0.7368421052631579,
"mmlu_loss": 1.074835775843177,
"step": 800
},
{
"epoch": 0.29,
"learning_rate": 0.0002,
"loss": 0.7028,
"step": 810
},
{
"epoch": 0.29,
"learning_rate": 0.0002,
"loss": 0.7465,
"step": 820
},
{
"epoch": 0.29,
"learning_rate": 0.0002,
"loss": 0.7717,
"step": 830
},
{
"epoch": 0.3,
"learning_rate": 0.0002,
"loss": 0.7256,
"step": 840
},
{
"epoch": 0.3,
"learning_rate": 0.0002,
"loss": 0.776,
"step": 850
},
{
"epoch": 0.3,
"learning_rate": 0.0002,
"loss": 0.7521,
"step": 860
},
{
"epoch": 0.31,
"learning_rate": 0.0002,
"loss": 0.7118,
"step": 870
},
{
"epoch": 0.31,
"learning_rate": 0.0002,
"loss": 0.6725,
"step": 880
},
{
"epoch": 0.31,
"learning_rate": 0.0002,
"loss": 0.6865,
"step": 890
},
{
"epoch": 0.32,
"learning_rate": 0.0002,
"loss": 0.7,
"step": 900
},
{
"epoch": 0.32,
"learning_rate": 0.0002,
"loss": 0.7387,
"step": 910
},
{
"epoch": 0.32,
"learning_rate": 0.0002,
"loss": 0.7117,
"step": 920
},
{
"epoch": 0.33,
"learning_rate": 0.0002,
"loss": 0.686,
"step": 930
},
{
"epoch": 0.33,
"learning_rate": 0.0002,
"loss": 0.7106,
"step": 940
},
{
"epoch": 0.34,
"learning_rate": 0.0002,
"loss": 0.7004,
"step": 950
},
{
"epoch": 0.34,
"learning_rate": 0.0002,
"loss": 0.7376,
"step": 960
},
{
"epoch": 0.34,
"learning_rate": 0.0002,
"loss": 0.7226,
"step": 970
},
{
"epoch": 0.35,
"learning_rate": 0.0002,
"loss": 0.7396,
"step": 980
},
{
"epoch": 0.35,
"learning_rate": 0.0002,
"loss": 0.7194,
"step": 990
},
{
"epoch": 0.35,
"learning_rate": 0.0002,
"loss": 0.7068,
"step": 1000
},
{
"epoch": 0.35,
"eval_loss": 0.7785887718200684,
"eval_runtime": 187.1264,
"eval_samples_per_second": 5.344,
"eval_steps_per_second": 2.672,
"step": 1000
},
{
"epoch": 0.35,
"mmlu_eval_accuracy": 0.4578914859636893,
"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": 0.4482758620689655,
"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": 0.2727272727272727,
"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": 0.3902439024390244,
"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": 0.2727272727272727,
"mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
"mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
"mmlu_eval_accuracy_high_school_geography": 0.7727272727272727,
"mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_macroeconomics": 0.3023255813953488,
"mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
"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": 0.30434782608695654,
"mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
"mmlu_eval_accuracy_high_school_world_history": 0.5,
"mmlu_eval_accuracy_human_aging": 0.6956521739130435,
"mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
"mmlu_eval_accuracy_international_law": 0.6923076923076923,
"mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
"mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
"mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
"mmlu_eval_accuracy_management": 0.6363636363636364,
"mmlu_eval_accuracy_marketing": 0.72,
"mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
"mmlu_eval_accuracy_miscellaneous": 0.6511627906976745,
"mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
"mmlu_eval_accuracy_moral_scenarios": 0.24,
"mmlu_eval_accuracy_nutrition": 0.5454545454545454,
"mmlu_eval_accuracy_philosophy": 0.5,
"mmlu_eval_accuracy_prehistory": 0.5142857142857142,
"mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
"mmlu_eval_accuracy_professional_law": 0.3411764705882353,
"mmlu_eval_accuracy_professional_medicine": 0.3870967741935484,
"mmlu_eval_accuracy_professional_psychology": 0.391304347826087,
"mmlu_eval_accuracy_public_relations": 0.6666666666666666,
"mmlu_eval_accuracy_security_studies": 0.5555555555555556,
"mmlu_eval_accuracy_sociology": 0.7272727272727273,
"mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
"mmlu_eval_accuracy_virology": 0.3888888888888889,
"mmlu_eval_accuracy_world_religions": 0.7368421052631579,
"mmlu_loss": 0.9906338841578979,
"step": 1000
},
{
"epoch": 0.36,
"learning_rate": 0.0002,
"loss": 0.7622,
"step": 1010
},
{
"epoch": 0.36,
"learning_rate": 0.0002,
"loss": 0.7039,
"step": 1020
},
{
"epoch": 0.36,
"learning_rate": 0.0002,
"loss": 0.7078,
"step": 1030
},
{
"epoch": 0.37,
"learning_rate": 0.0002,
"loss": 0.7504,
"step": 1040
},
{
"epoch": 0.37,
"learning_rate": 0.0002,
"loss": 0.7543,
"step": 1050
},
{
"epoch": 0.37,
"learning_rate": 0.0002,
"loss": 0.7081,
"step": 1060
},
{
"epoch": 0.38,
"learning_rate": 0.0002,
"loss": 0.7193,
"step": 1070
},
{
"epoch": 0.38,
"learning_rate": 0.0002,
"loss": 0.7138,
"step": 1080
},
{
"epoch": 0.38,
"learning_rate": 0.0002,
"loss": 0.7277,
"step": 1090
},
{
"epoch": 0.39,
"learning_rate": 0.0002,
"loss": 0.7183,
"step": 1100
},
{
"epoch": 0.39,
"learning_rate": 0.0002,
"loss": 0.6955,
"step": 1110
},
{
"epoch": 0.4,
"learning_rate": 0.0002,
"loss": 0.6558,
"step": 1120
},
{
"epoch": 0.4,
"learning_rate": 0.0002,
"loss": 0.7213,
"step": 1130
},
{
"epoch": 0.4,
"learning_rate": 0.0002,
"loss": 0.7377,
"step": 1140
},
{
"epoch": 0.41,
"learning_rate": 0.0002,
"loss": 0.7591,
"step": 1150
},
{
"epoch": 0.41,
"learning_rate": 0.0002,
"loss": 0.7336,
"step": 1160
},
{
"epoch": 0.41,
"learning_rate": 0.0002,
"loss": 0.717,
"step": 1170
},
{
"epoch": 0.42,
"learning_rate": 0.0002,
"loss": 0.6958,
"step": 1180
},
{
"epoch": 0.42,
"learning_rate": 0.0002,
"loss": 0.6692,
"step": 1190
},
{
"epoch": 0.42,
"learning_rate": 0.0002,
"loss": 0.6991,
"step": 1200
},
{
"epoch": 0.42,
"eval_loss": 0.7757567167282104,
"eval_runtime": 186.5318,
"eval_samples_per_second": 5.361,
"eval_steps_per_second": 2.681,
"step": 1200
},
{
"epoch": 0.42,
"mmlu_eval_accuracy": 0.4543617194438492,
"mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
"mmlu_eval_accuracy_anatomy": 0.5,
"mmlu_eval_accuracy_astronomy": 0.5625,
"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": 0.0,
"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": 0.36585365853658536,
"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": 0.36363636363636365,
"mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
"mmlu_eval_accuracy_high_school_european_history": 0.7222222222222222,
"mmlu_eval_accuracy_high_school_geography": 0.7272727272727273,
"mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_macroeconomics": 0.3023255813953488,
"mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
"mmlu_eval_accuracy_high_school_microeconomics": 0.34615384615384615,
"mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
"mmlu_eval_accuracy_high_school_psychology": 0.75,
"mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
"mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
"mmlu_eval_accuracy_high_school_world_history": 0.5384615384615384,
"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": 0.36363636363636365,
"mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
"mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
"mmlu_eval_accuracy_management": 0.6363636363636364,
"mmlu_eval_accuracy_marketing": 0.68,
"mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
"mmlu_eval_accuracy_miscellaneous": 0.6511627906976745,
"mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
"mmlu_eval_accuracy_moral_scenarios": 0.24,
"mmlu_eval_accuracy_nutrition": 0.6060606060606061,
"mmlu_eval_accuracy_philosophy": 0.47058823529411764,
"mmlu_eval_accuracy_prehistory": 0.45714285714285713,
"mmlu_eval_accuracy_professional_accounting": 0.3548387096774194,
"mmlu_eval_accuracy_professional_law": 0.3352941176470588,
"mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
"mmlu_eval_accuracy_professional_psychology": 0.4057971014492754,
"mmlu_eval_accuracy_public_relations": 0.5,
"mmlu_eval_accuracy_security_studies": 0.5185185185185185,
"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": 0.6842105263157895,
"mmlu_loss": 1.0648847781608062,
"step": 1200
},
{
"epoch": 0.43,
"learning_rate": 0.0002,
"loss": 0.7593,
"step": 1210
},
{
"epoch": 0.43,
"learning_rate": 0.0002,
"loss": 0.6822,
"step": 1220
},
{
"epoch": 0.43,
"learning_rate": 0.0002,
"loss": 0.699,
"step": 1230
},
{
"epoch": 0.44,
"learning_rate": 0.0002,
"loss": 0.7015,
"step": 1240
},
{
"epoch": 0.44,
"learning_rate": 0.0002,
"loss": 0.6901,
"step": 1250
},
{
"epoch": 0.44,
"learning_rate": 0.0002,
"loss": 0.7406,
"step": 1260
},
{
"epoch": 0.45,
"learning_rate": 0.0002,
"loss": 0.6947,
"step": 1270
},
{
"epoch": 0.45,
"learning_rate": 0.0002,
"loss": 0.734,
"step": 1280
},
{
"epoch": 0.46,
"learning_rate": 0.0002,
"loss": 0.7335,
"step": 1290
},
{
"epoch": 0.46,
"learning_rate": 0.0002,
"loss": 0.7067,
"step": 1300
},
{
"epoch": 0.46,
"learning_rate": 0.0002,
"loss": 0.7627,
"step": 1310
},
{
"epoch": 0.47,
"learning_rate": 0.0002,
"loss": 0.676,
"step": 1320
},
{
"epoch": 0.47,
"learning_rate": 0.0002,
"loss": 0.7385,
"step": 1330
},
{
"epoch": 0.47,
"learning_rate": 0.0002,
"loss": 0.6752,
"step": 1340
},
{
"epoch": 0.48,
"learning_rate": 0.0002,
"loss": 0.7385,
"step": 1350
},
{
"epoch": 0.48,
"learning_rate": 0.0002,
"loss": 0.7122,
"step": 1360
},
{
"epoch": 0.48,
"learning_rate": 0.0002,
"loss": 0.6792,
"step": 1370
},
{
"epoch": 0.49,
"learning_rate": 0.0002,
"loss": 0.6761,
"step": 1380
},
{
"epoch": 0.49,
"learning_rate": 0.0002,
"loss": 0.7069,
"step": 1390
},
{
"epoch": 0.49,
"learning_rate": 0.0002,
"loss": 0.7067,
"step": 1400
},
{
"epoch": 0.49,
"eval_loss": 0.7749121189117432,
"eval_runtime": 186.6278,
"eval_samples_per_second": 5.358,
"eval_steps_per_second": 2.679,
"step": 1400
},
{
"epoch": 0.49,
"mmlu_eval_accuracy": 0.4656455181567258,
"mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
"mmlu_eval_accuracy_anatomy": 0.5,
"mmlu_eval_accuracy_astronomy": 0.5,
"mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
"mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655,
"mmlu_eval_accuracy_college_biology": 0.4375,
"mmlu_eval_accuracy_college_chemistry": 0.125,
"mmlu_eval_accuracy_college_computer_science": 0.45454545454545453,
"mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
"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": 0.3902439024390244,
"mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
"mmlu_eval_accuracy_global_facts": 0.5,
"mmlu_eval_accuracy_high_school_biology": 0.375,
"mmlu_eval_accuracy_high_school_chemistry": 0.36363636363636365,
"mmlu_eval_accuracy_high_school_computer_science": 0.7777777777777778,
"mmlu_eval_accuracy_high_school_european_history": 0.7222222222222222,
"mmlu_eval_accuracy_high_school_geography": 0.7272727272727273,
"mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_macroeconomics": 0.3023255813953488,
"mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
"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": 0.391304347826087,
"mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
"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": 0.36363636363636365,
"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": 0.4473684210526316,
"mmlu_eval_accuracy_moral_scenarios": 0.23,
"mmlu_eval_accuracy_nutrition": 0.5454545454545454,
"mmlu_eval_accuracy_philosophy": 0.5,
"mmlu_eval_accuracy_prehistory": 0.4,
"mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
"mmlu_eval_accuracy_professional_law": 0.3235294117647059,
"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": 0.48148148148148145,
"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": 0.7368421052631579,
"mmlu_loss": 1.0056204651883627,
"step": 1400
},
{
"epoch": 0.5,
"learning_rate": 0.0002,
"loss": 0.672,
"step": 1410
},
{
"epoch": 0.5,
"learning_rate": 0.0002,
"loss": 0.6638,
"step": 1420
},
{
"epoch": 0.5,
"learning_rate": 0.0002,
"loss": 0.7447,
"step": 1430
},
{
"epoch": 0.51,
"learning_rate": 0.0002,
"loss": 0.703,
"step": 1440
},
{
"epoch": 0.51,
"learning_rate": 0.0002,
"loss": 0.6834,
"step": 1450
},
{
"epoch": 0.52,
"learning_rate": 0.0002,
"loss": 0.7059,
"step": 1460
},
{
"epoch": 0.52,
"learning_rate": 0.0002,
"loss": 0.7046,
"step": 1470
},
{
"epoch": 0.52,
"learning_rate": 0.0002,
"loss": 0.7405,
"step": 1480
},
{
"epoch": 0.53,
"learning_rate": 0.0002,
"loss": 0.6708,
"step": 1490
},
{
"epoch": 0.53,
"learning_rate": 0.0002,
"loss": 0.7534,
"step": 1500
},
{
"epoch": 0.53,
"learning_rate": 0.0002,
"loss": 0.7192,
"step": 1510
},
{
"epoch": 0.54,
"learning_rate": 0.0002,
"loss": 0.7252,
"step": 1520
},
{
"epoch": 0.54,
"learning_rate": 0.0002,
"loss": 0.6876,
"step": 1530
},
{
"epoch": 0.54,
"learning_rate": 0.0002,
"loss": 0.6603,
"step": 1540
},
{
"epoch": 0.55,
"learning_rate": 0.0002,
"loss": 0.6957,
"step": 1550
},
{
"epoch": 0.55,
"learning_rate": 0.0002,
"loss": 0.7745,
"step": 1560
},
{
"epoch": 0.55,
"learning_rate": 0.0002,
"loss": 0.7035,
"step": 1570
},
{
"epoch": 0.56,
"learning_rate": 0.0002,
"loss": 0.7381,
"step": 1580
},
{
"epoch": 0.56,
"learning_rate": 0.0002,
"loss": 0.6919,
"step": 1590
},
{
"epoch": 0.56,
"learning_rate": 0.0002,
"loss": 0.6665,
"step": 1600
},
{
"epoch": 0.56,
"eval_loss": 0.7732749581336975,
"eval_runtime": 189.0558,
"eval_samples_per_second": 5.289,
"eval_steps_per_second": 2.645,
"step": 1600
},
{
"epoch": 0.56,
"mmlu_eval_accuracy": 0.4643913679545894,
"mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
"mmlu_eval_accuracy_anatomy": 0.5,
"mmlu_eval_accuracy_astronomy": 0.5,
"mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
"mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655,
"mmlu_eval_accuracy_college_biology": 0.3125,
"mmlu_eval_accuracy_college_chemistry": 0.375,
"mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
"mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
"mmlu_eval_accuracy_college_medicine": 0.4090909090909091,
"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": 0.25,
"mmlu_eval_accuracy_electrical_engineering": 0.4375,
"mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
"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": 0.36363636363636365,
"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": 0.3023255813953488,
"mmlu_eval_accuracy_high_school_mathematics": 0.1724137931034483,
"mmlu_eval_accuracy_high_school_microeconomics": 0.4230769230769231,
"mmlu_eval_accuracy_high_school_physics": 0.35294117647058826,
"mmlu_eval_accuracy_high_school_psychology": 0.6833333333333333,
"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": 0.6521739130434783,
"mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
"mmlu_eval_accuracy_international_law": 0.6923076923076923,
"mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
"mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
"mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
"mmlu_eval_accuracy_management": 0.6363636363636364,
"mmlu_eval_accuracy_marketing": 0.68,
"mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
"mmlu_eval_accuracy_miscellaneous": 0.6976744186046512,
"mmlu_eval_accuracy_moral_disputes": 0.42105263157894735,
"mmlu_eval_accuracy_moral_scenarios": 0.24,
"mmlu_eval_accuracy_nutrition": 0.5757575757575758,
"mmlu_eval_accuracy_philosophy": 0.47058823529411764,
"mmlu_eval_accuracy_prehistory": 0.45714285714285713,
"mmlu_eval_accuracy_professional_accounting": 0.3870967741935484,
"mmlu_eval_accuracy_professional_law": 0.32941176470588235,
"mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
"mmlu_eval_accuracy_professional_psychology": 0.391304347826087,
"mmlu_eval_accuracy_public_relations": 0.5,
"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": 0.3888888888888889,
"mmlu_eval_accuracy_world_religions": 0.7368421052631579,
"mmlu_loss": 1.211870277013542,
"step": 1600
},
{
"epoch": 0.57,
"learning_rate": 0.0002,
"loss": 0.6885,
"step": 1610
},
{
"epoch": 0.57,
"learning_rate": 0.0002,
"loss": 0.6468,
"step": 1620
},
{
"epoch": 0.58,
"learning_rate": 0.0002,
"loss": 0.6762,
"step": 1630
},
{
"epoch": 0.58,
"learning_rate": 0.0002,
"loss": 0.7359,
"step": 1640
},
{
"epoch": 0.58,
"learning_rate": 0.0002,
"loss": 0.7327,
"step": 1650
},
{
"epoch": 0.59,
"learning_rate": 0.0002,
"loss": 0.6205,
"step": 1660
},
{
"epoch": 0.59,
"learning_rate": 0.0002,
"loss": 0.7413,
"step": 1670
},
{
"epoch": 0.59,
"learning_rate": 0.0002,
"loss": 0.7164,
"step": 1680
},
{
"epoch": 0.6,
"learning_rate": 0.0002,
"loss": 0.6865,
"step": 1690
},
{
"epoch": 0.6,
"learning_rate": 0.0002,
"loss": 0.6713,
"step": 1700
},
{
"epoch": 0.6,
"learning_rate": 0.0002,
"loss": 0.6729,
"step": 1710
},
{
"epoch": 0.61,
"learning_rate": 0.0002,
"loss": 0.6604,
"step": 1720
},
{
"epoch": 0.61,
"learning_rate": 0.0002,
"loss": 0.6889,
"step": 1730
},
{
"epoch": 0.61,
"learning_rate": 0.0002,
"loss": 0.726,
"step": 1740
},
{
"epoch": 0.62,
"learning_rate": 0.0002,
"loss": 0.7183,
"step": 1750
},
{
"epoch": 0.62,
"learning_rate": 0.0002,
"loss": 0.6994,
"step": 1760
},
{
"epoch": 0.62,
"learning_rate": 0.0002,
"loss": 0.6921,
"step": 1770
},
{
"epoch": 0.63,
"learning_rate": 0.0002,
"loss": 0.6768,
"step": 1780
},
{
"epoch": 0.63,
"learning_rate": 0.0002,
"loss": 0.7288,
"step": 1790
},
{
"epoch": 0.63,
"learning_rate": 0.0002,
"loss": 0.6793,
"step": 1800
},
{
"epoch": 0.63,
"eval_loss": 0.769940197467804,
"eval_runtime": 188.6588,
"eval_samples_per_second": 5.301,
"eval_steps_per_second": 2.65,
"step": 1800
},
{
"epoch": 0.63,
"mmlu_eval_accuracy": 0.4624357023236349,
"mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
"mmlu_eval_accuracy_anatomy": 0.5,
"mmlu_eval_accuracy_astronomy": 0.5,
"mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
"mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655,
"mmlu_eval_accuracy_college_biology": 0.3125,
"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": 0.45454545454545453,
"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": 0.2857142857142857,
"mmlu_eval_accuracy_global_facts": 0.6,
"mmlu_eval_accuracy_high_school_biology": 0.375,
"mmlu_eval_accuracy_high_school_chemistry": 0.36363636363636365,
"mmlu_eval_accuracy_high_school_computer_science": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_geography": 0.7272727272727273,
"mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_macroeconomics": 0.3023255813953488,
"mmlu_eval_accuracy_high_school_mathematics": 0.1724137931034483,
"mmlu_eval_accuracy_high_school_microeconomics": 0.38461538461538464,
"mmlu_eval_accuracy_high_school_physics": 0.35294117647058826,
"mmlu_eval_accuracy_high_school_psychology": 0.7,
"mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
"mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
"mmlu_eval_accuracy_high_school_world_history": 0.5,
"mmlu_eval_accuracy_human_aging": 0.6956521739130435,
"mmlu_eval_accuracy_human_sexuality": 0.5,
"mmlu_eval_accuracy_international_law": 0.6923076923076923,
"mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
"mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
"mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
"mmlu_eval_accuracy_management": 0.6363636363636364,
"mmlu_eval_accuracy_marketing": 0.72,
"mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
"mmlu_eval_accuracy_miscellaneous": 0.6744186046511628,
"mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
"mmlu_eval_accuracy_moral_scenarios": 0.24,
"mmlu_eval_accuracy_nutrition": 0.5454545454545454,
"mmlu_eval_accuracy_philosophy": 0.4411764705882353,
"mmlu_eval_accuracy_prehistory": 0.4857142857142857,
"mmlu_eval_accuracy_professional_accounting": 0.3548387096774194,
"mmlu_eval_accuracy_professional_law": 0.3176470588235294,
"mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
"mmlu_eval_accuracy_professional_psychology": 0.4057971014492754,
"mmlu_eval_accuracy_public_relations": 0.4166666666666667,
"mmlu_eval_accuracy_security_studies": 0.5185185185185185,
"mmlu_eval_accuracy_sociology": 0.7272727272727273,
"mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
"mmlu_eval_accuracy_virology": 0.4444444444444444,
"mmlu_eval_accuracy_world_religions": 0.6842105263157895,
"mmlu_loss": 1.171973392095018,
"step": 1800
},
{
"epoch": 0.64,
"learning_rate": 0.0002,
"loss": 0.7021,
"step": 1810
},
{
"epoch": 0.64,
"learning_rate": 0.0002,
"loss": 0.6696,
"step": 1820
},
{
"epoch": 0.65,
"learning_rate": 0.0002,
"loss": 0.7099,
"step": 1830
},
{
"epoch": 0.65,
"learning_rate": 0.0002,
"loss": 0.7604,
"step": 1840
},
{
"epoch": 0.65,
"learning_rate": 0.0002,
"loss": 0.6885,
"step": 1850
},
{
"epoch": 0.66,
"learning_rate": 0.0002,
"loss": 0.6649,
"step": 1860
},
{
"epoch": 0.66,
"learning_rate": 0.0002,
"loss": 0.7325,
"step": 1870
},
{
"epoch": 0.66,
"learning_rate": 0.0002,
"loss": 0.6309,
"step": 1880
},
{
"epoch": 0.67,
"learning_rate": 0.0002,
"loss": 0.7024,
"step": 1890
},
{
"epoch": 0.67,
"learning_rate": 0.0002,
"loss": 0.6719,
"step": 1900
},
{
"epoch": 0.67,
"learning_rate": 0.0002,
"loss": 0.683,
"step": 1910
},
{
"epoch": 0.68,
"learning_rate": 0.0002,
"loss": 0.6862,
"step": 1920
},
{
"epoch": 0.68,
"learning_rate": 0.0002,
"loss": 0.7632,
"step": 1930
},
{
"epoch": 0.68,
"learning_rate": 0.0002,
"loss": 0.7087,
"step": 1940
},
{
"epoch": 0.69,
"learning_rate": 0.0002,
"loss": 0.6527,
"step": 1950
},
{
"epoch": 0.69,
"learning_rate": 0.0002,
"loss": 0.7284,
"step": 1960
},
{
"epoch": 0.69,
"learning_rate": 0.0002,
"loss": 0.6579,
"step": 1970
},
{
"epoch": 0.7,
"learning_rate": 0.0002,
"loss": 0.7191,
"step": 1980
},
{
"epoch": 0.7,
"learning_rate": 0.0002,
"loss": 0.6849,
"step": 1990
},
{
"epoch": 0.71,
"learning_rate": 0.0002,
"loss": 0.7375,
"step": 2000
},
{
"epoch": 0.71,
"eval_loss": 0.769704282283783,
"eval_runtime": 188.6001,
"eval_samples_per_second": 5.302,
"eval_steps_per_second": 2.651,
"step": 2000
},
{
"epoch": 0.71,
"mmlu_eval_accuracy": 0.4586122911114159,
"mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
"mmlu_eval_accuracy_anatomy": 0.5,
"mmlu_eval_accuracy_astronomy": 0.5625,
"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": 0.4230769230769231,
"mmlu_eval_accuracy_econometrics": 0.16666666666666666,
"mmlu_eval_accuracy_electrical_engineering": 0.3125,
"mmlu_eval_accuracy_elementary_mathematics": 0.36585365853658536,
"mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
"mmlu_eval_accuracy_global_facts": 0.4,
"mmlu_eval_accuracy_high_school_biology": 0.4375,
"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": 0.7727272727272727,
"mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
"mmlu_eval_accuracy_high_school_macroeconomics": 0.3023255813953488,
"mmlu_eval_accuracy_high_school_mathematics": 0.1724137931034483,
"mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156,
"mmlu_eval_accuracy_high_school_physics": 0.35294117647058826,
"mmlu_eval_accuracy_high_school_psychology": 0.6833333333333333,
"mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
"mmlu_eval_accuracy_high_school_us_history": 0.5454545454545454,
"mmlu_eval_accuracy_high_school_world_history": 0.5384615384615384,
"mmlu_eval_accuracy_human_aging": 0.6956521739130435,
"mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
"mmlu_eval_accuracy_international_law": 0.7692307692307693,
"mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
"mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
"mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
"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": 0.23,
"mmlu_eval_accuracy_nutrition": 0.5757575757575758,
"mmlu_eval_accuracy_philosophy": 0.47058823529411764,
"mmlu_eval_accuracy_prehistory": 0.42857142857142855,
"mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
"mmlu_eval_accuracy_professional_law": 0.3235294117647059,
"mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
"mmlu_eval_accuracy_professional_psychology": 0.391304347826087,
"mmlu_eval_accuracy_public_relations": 0.5,
"mmlu_eval_accuracy_security_studies": 0.5555555555555556,
"mmlu_eval_accuracy_sociology": 0.6818181818181818,
"mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
"mmlu_eval_accuracy_virology": 0.4444444444444444,
"mmlu_eval_accuracy_world_religions": 0.7368421052631579,
"mmlu_loss": 1.1570235493911465,
"step": 2000
},
{
"epoch": 0.71,
"learning_rate": 0.0002,
"loss": 0.6536,
"step": 2010
},
{
"epoch": 0.71,
"learning_rate": 0.0002,
"loss": 0.6591,
"step": 2020
},
{
"epoch": 0.72,
"learning_rate": 0.0002,
"loss": 0.7033,
"step": 2030
},
{
"epoch": 0.72,
"learning_rate": 0.0002,
"loss": 0.7312,
"step": 2040
},
{
"epoch": 0.72,
"learning_rate": 0.0002,
"loss": 0.7322,
"step": 2050
},
{
"epoch": 0.73,
"learning_rate": 0.0002,
"loss": 0.7249,
"step": 2060
},
{
"epoch": 0.73,
"learning_rate": 0.0002,
"loss": 0.7576,
"step": 2070
},
{
"epoch": 0.73,
"learning_rate": 0.0002,
"loss": 0.7499,
"step": 2080
},
{
"epoch": 0.74,
"learning_rate": 0.0002,
"loss": 0.6414,
"step": 2090
},
{
"epoch": 0.74,
"learning_rate": 0.0002,
"loss": 0.7201,
"step": 2100
},
{
"epoch": 0.74,
"learning_rate": 0.0002,
"loss": 0.6904,
"step": 2110
},
{
"epoch": 0.75,
"learning_rate": 0.0002,
"loss": 0.716,
"step": 2120
},
{
"epoch": 0.75,
"learning_rate": 0.0002,
"loss": 0.6923,
"step": 2130
},
{
"epoch": 0.75,
"learning_rate": 0.0002,
"loss": 0.7509,
"step": 2140
},
{
"epoch": 0.76,
"learning_rate": 0.0002,
"loss": 0.7288,
"step": 2150
},
{
"epoch": 0.76,
"learning_rate": 0.0002,
"loss": 0.6475,
"step": 2160
},
{
"epoch": 0.77,
"learning_rate": 0.0002,
"loss": 0.6637,
"step": 2170
},
{
"epoch": 0.77,
"learning_rate": 0.0002,
"loss": 0.7629,
"step": 2180
},
{
"epoch": 0.77,
"learning_rate": 0.0002,
"loss": 0.6744,
"step": 2190
},
{
"epoch": 0.78,
"learning_rate": 0.0002,
"loss": 0.7216,
"step": 2200
},
{
"epoch": 0.78,
"eval_loss": 0.7676219344139099,
"eval_runtime": 186.1144,
"eval_samples_per_second": 5.373,
"eval_steps_per_second": 2.687,
"step": 2200
},
{
"epoch": 0.78,
"mmlu_eval_accuracy": 0.4688920828630079,
"mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
"mmlu_eval_accuracy_anatomy": 0.5,
"mmlu_eval_accuracy_astronomy": 0.5,
"mmlu_eval_accuracy_business_ethics": 0.6363636363636364,
"mmlu_eval_accuracy_clinical_knowledge": 0.41379310344827586,
"mmlu_eval_accuracy_college_biology": 0.3125,
"mmlu_eval_accuracy_college_chemistry": 0.375,
"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": 0.45454545454545453,
"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": 0.375,
"mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
"mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
"mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
"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": 0.65,
"mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
"mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
"mmlu_eval_accuracy_high_school_world_history": 0.5384615384615384,
"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": 0.36363636363636365,
"mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
"mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
"mmlu_eval_accuracy_management": 0.6363636363636364,
"mmlu_eval_accuracy_marketing": 0.72,
"mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
"mmlu_eval_accuracy_miscellaneous": 0.686046511627907,
"mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
"mmlu_eval_accuracy_moral_scenarios": 0.24,
"mmlu_eval_accuracy_nutrition": 0.6060606060606061,
"mmlu_eval_accuracy_philosophy": 0.4411764705882353,
"mmlu_eval_accuracy_prehistory": 0.45714285714285713,
"mmlu_eval_accuracy_professional_accounting": 0.3225806451612903,
"mmlu_eval_accuracy_professional_law": 0.3058823529411765,
"mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
"mmlu_eval_accuracy_professional_psychology": 0.42028985507246375,
"mmlu_eval_accuracy_public_relations": 0.3333333333333333,
"mmlu_eval_accuracy_security_studies": 0.5555555555555556,
"mmlu_eval_accuracy_sociology": 0.7272727272727273,
"mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
"mmlu_eval_accuracy_virology": 0.5555555555555556,
"mmlu_eval_accuracy_world_religions": 0.7368421052631579,
"mmlu_loss": 1.2998772347564798,
"step": 2200
},
{
"epoch": 0.78,
"learning_rate": 0.0002,
"loss": 0.6914,
"step": 2210
},
{
"epoch": 0.78,
"learning_rate": 0.0002,
"loss": 0.6982,
"step": 2220
},
{
"epoch": 0.79,
"learning_rate": 0.0002,
"loss": 0.7011,
"step": 2230
},
{
"epoch": 0.79,
"learning_rate": 0.0002,
"loss": 0.7204,
"step": 2240
},
{
"epoch": 0.79,
"learning_rate": 0.0002,
"loss": 0.7029,
"step": 2250
},
{
"epoch": 0.8,
"learning_rate": 0.0002,
"loss": 0.6997,
"step": 2260
},
{
"epoch": 0.8,
"learning_rate": 0.0002,
"loss": 0.7481,
"step": 2270
},
{
"epoch": 0.8,
"learning_rate": 0.0002,
"loss": 0.6893,
"step": 2280
},
{
"epoch": 0.81,
"learning_rate": 0.0002,
"loss": 0.7546,
"step": 2290
},
{
"epoch": 0.81,
"learning_rate": 0.0002,
"loss": 0.6735,
"step": 2300
},
{
"epoch": 0.81,
"learning_rate": 0.0002,
"loss": 0.695,
"step": 2310
},
{
"epoch": 0.82,
"learning_rate": 0.0002,
"loss": 0.7171,
"step": 2320
},
{
"epoch": 0.82,
"learning_rate": 0.0002,
"loss": 0.6942,
"step": 2330
},
{
"epoch": 0.83,
"learning_rate": 0.0002,
"loss": 0.6779,
"step": 2340
},
{
"epoch": 0.83,
"learning_rate": 0.0002,
"loss": 0.7155,
"step": 2350
},
{
"epoch": 0.83,
"learning_rate": 0.0002,
"loss": 0.6583,
"step": 2360
},
{
"epoch": 0.84,
"learning_rate": 0.0002,
"loss": 0.6599,
"step": 2370
},
{
"epoch": 0.84,
"learning_rate": 0.0002,
"loss": 0.8043,
"step": 2380
},
{
"epoch": 0.84,
"learning_rate": 0.0002,
"loss": 0.6276,
"step": 2390
},
{
"epoch": 0.85,
"learning_rate": 0.0002,
"loss": 0.6935,
"step": 2400
},
{
"epoch": 0.85,
"eval_loss": 0.7674869298934937,
"eval_runtime": 186.2898,
"eval_samples_per_second": 5.368,
"eval_steps_per_second": 2.684,
"step": 2400
},
{
"epoch": 0.85,
"mmlu_eval_accuracy": 0.4624483299799015,
"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": 0.375,
"mmlu_eval_accuracy_college_chemistry": 0.25,
"mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
"mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
"mmlu_eval_accuracy_college_medicine": 0.36363636363636365,
"mmlu_eval_accuracy_college_physics": 0.45454545454545453,
"mmlu_eval_accuracy_computer_security": 0.45454545454545453,
"mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
"mmlu_eval_accuracy_econometrics": 0.16666666666666666,
"mmlu_eval_accuracy_electrical_engineering": 0.4375,
"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": 0.40625,
"mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
"mmlu_eval_accuracy_high_school_computer_science": 0.4444444444444444,
"mmlu_eval_accuracy_high_school_european_history": 0.5,
"mmlu_eval_accuracy_high_school_geography": 0.8181818181818182,
"mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
"mmlu_eval_accuracy_high_school_macroeconomics": 0.3023255813953488,
"mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
"mmlu_eval_accuracy_high_school_microeconomics": 0.4230769230769231,
"mmlu_eval_accuracy_high_school_physics": 0.35294117647058826,
"mmlu_eval_accuracy_high_school_psychology": 0.6833333333333333,
"mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
"mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
"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": 0.6923076923076923,
"mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
"mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
"mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
"mmlu_eval_accuracy_management": 0.6363636363636364,
"mmlu_eval_accuracy_marketing": 0.76,
"mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
"mmlu_eval_accuracy_miscellaneous": 0.6744186046511628,
"mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
"mmlu_eval_accuracy_moral_scenarios": 0.24,
"mmlu_eval_accuracy_nutrition": 0.6060606060606061,
"mmlu_eval_accuracy_philosophy": 0.5294117647058824,
"mmlu_eval_accuracy_prehistory": 0.4857142857142857,
"mmlu_eval_accuracy_professional_accounting": 0.3548387096774194,
"mmlu_eval_accuracy_professional_law": 0.3176470588235294,
"mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
"mmlu_eval_accuracy_professional_psychology": 0.4057971014492754,
"mmlu_eval_accuracy_public_relations": 0.3333333333333333,
"mmlu_eval_accuracy_security_studies": 0.5925925925925926,
"mmlu_eval_accuracy_sociology": 0.7272727272727273,
"mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
"mmlu_eval_accuracy_virology": 0.3888888888888889,
"mmlu_eval_accuracy_world_religions": 0.7368421052631579,
"mmlu_loss": 1.1521158476722457,
"step": 2400
},
{
"epoch": 0.85,
"learning_rate": 0.0002,
"loss": 0.6884,
"step": 2410
},
{
"epoch": 0.85,
"learning_rate": 0.0002,
"loss": 0.6951,
"step": 2420
},
{
"epoch": 0.86,
"learning_rate": 0.0002,
"loss": 0.6889,
"step": 2430
},
{
"epoch": 0.86,
"learning_rate": 0.0002,
"loss": 0.6504,
"step": 2440
},
{
"epoch": 0.86,
"learning_rate": 0.0002,
"loss": 0.7216,
"step": 2450
},
{
"epoch": 0.87,
"learning_rate": 0.0002,
"loss": 0.6864,
"step": 2460
},
{
"epoch": 0.87,
"learning_rate": 0.0002,
"loss": 0.6508,
"step": 2470
},
{
"epoch": 0.87,
"learning_rate": 0.0002,
"loss": 0.6698,
"step": 2480
},
{
"epoch": 0.88,
"learning_rate": 0.0002,
"loss": 0.7087,
"step": 2490
},
{
"epoch": 0.88,
"learning_rate": 0.0002,
"loss": 0.6714,
"step": 2500
},
{
"epoch": 0.89,
"learning_rate": 0.0002,
"loss": 0.7352,
"step": 2510
},
{
"epoch": 0.89,
"learning_rate": 0.0002,
"loss": 0.7212,
"step": 2520
},
{
"epoch": 0.89,
"learning_rate": 0.0002,
"loss": 0.6869,
"step": 2530
},
{
"epoch": 0.9,
"learning_rate": 0.0002,
"loss": 0.6961,
"step": 2540
},
{
"epoch": 0.9,
"learning_rate": 0.0002,
"loss": 0.7009,
"step": 2550
},
{
"epoch": 0.9,
"learning_rate": 0.0002,
"loss": 0.7227,
"step": 2560
},
{
"epoch": 0.91,
"learning_rate": 0.0002,
"loss": 0.6833,
"step": 2570
},
{
"epoch": 0.91,
"learning_rate": 0.0002,
"loss": 0.7468,
"step": 2580
},
{
"epoch": 0.91,
"learning_rate": 0.0002,
"loss": 0.7568,
"step": 2590
},
{
"epoch": 0.92,
"learning_rate": 0.0002,
"loss": 0.7271,
"step": 2600
},
{
"epoch": 0.92,
"eval_loss": 0.7648921012878418,
"eval_runtime": 185.3553,
"eval_samples_per_second": 5.395,
"eval_steps_per_second": 2.698,
"step": 2600
},
{
"epoch": 0.92,
"mmlu_eval_accuracy": 0.4649620294296765,
"mmlu_eval_accuracy_abstract_algebra": 0.45454545454545453,
"mmlu_eval_accuracy_anatomy": 0.5714285714285714,
"mmlu_eval_accuracy_astronomy": 0.5,
"mmlu_eval_accuracy_business_ethics": 0.6363636363636364,
"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": 0.36363636363636365,
"mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
"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": 0.08333333333333333,
"mmlu_eval_accuracy_electrical_engineering": 0.3125,
"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": 0.4375,
"mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
"mmlu_eval_accuracy_high_school_computer_science": 0.4444444444444444,
"mmlu_eval_accuracy_high_school_european_history": 0.5,
"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": 0.1724137931034483,
"mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156,
"mmlu_eval_accuracy_high_school_physics": 0.35294117647058826,
"mmlu_eval_accuracy_high_school_psychology": 0.7,
"mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
"mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
"mmlu_eval_accuracy_high_school_world_history": 0.5769230769230769,
"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": 0.36363636363636365,
"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": 0.686046511627907,
"mmlu_eval_accuracy_moral_disputes": 0.5263157894736842,
"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": 0.2903225806451613,
"mmlu_eval_accuracy_professional_law": 0.3235294117647059,
"mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
"mmlu_eval_accuracy_professional_psychology": 0.42028985507246375,
"mmlu_eval_accuracy_public_relations": 0.5,
"mmlu_eval_accuracy_security_studies": 0.5555555555555556,
"mmlu_eval_accuracy_sociology": 0.6818181818181818,
"mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
"mmlu_eval_accuracy_virology": 0.5,
"mmlu_eval_accuracy_world_religions": 0.7368421052631579,
"mmlu_loss": 1.3137481814109315,
"step": 2600
},
{
"epoch": 0.92,
"learning_rate": 0.0002,
"loss": 0.7144,
"step": 2610
},
{
"epoch": 0.92,
"learning_rate": 0.0002,
"loss": 0.7213,
"step": 2620
},
{
"epoch": 0.93,
"learning_rate": 0.0002,
"loss": 0.685,
"step": 2630
},
{
"epoch": 0.93,
"learning_rate": 0.0002,
"loss": 0.6937,
"step": 2640
},
{
"epoch": 0.93,
"learning_rate": 0.0002,
"loss": 0.7367,
"step": 2650
},
{
"epoch": 0.94,
"learning_rate": 0.0002,
"loss": 0.7221,
"step": 2660
},
{
"epoch": 0.94,
"learning_rate": 0.0002,
"loss": 0.717,
"step": 2670
},
{
"epoch": 0.95,
"learning_rate": 0.0002,
"loss": 0.6915,
"step": 2680
},
{
"epoch": 0.95,
"learning_rate": 0.0002,
"loss": 0.6913,
"step": 2690
},
{
"epoch": 0.95,
"learning_rate": 0.0002,
"loss": 0.6552,
"step": 2700
},
{
"epoch": 0.96,
"learning_rate": 0.0002,
"loss": 0.7508,
"step": 2710
},
{
"epoch": 0.96,
"learning_rate": 0.0002,
"loss": 0.6657,
"step": 2720
},
{
"epoch": 0.96,
"learning_rate": 0.0002,
"loss": 0.7466,
"step": 2730
},
{
"epoch": 0.97,
"learning_rate": 0.0002,
"loss": 0.7433,
"step": 2740
},
{
"epoch": 0.97,
"learning_rate": 0.0002,
"loss": 0.7041,
"step": 2750
},
{
"epoch": 0.97,
"learning_rate": 0.0002,
"loss": 0.7001,
"step": 2760
},
{
"epoch": 0.98,
"learning_rate": 0.0002,
"loss": 0.6845,
"step": 2770
},
{
"epoch": 0.98,
"learning_rate": 0.0002,
"loss": 0.7031,
"step": 2780
},
{
"epoch": 0.98,
"learning_rate": 0.0002,
"loss": 0.7454,
"step": 2790
},
{
"epoch": 0.99,
"learning_rate": 0.0002,
"loss": 0.7136,
"step": 2800
},
{
"epoch": 0.99,
"eval_loss": 0.7639025449752808,
"eval_runtime": 184.2838,
"eval_samples_per_second": 5.426,
"eval_steps_per_second": 2.713,
"step": 2800
},
{
"epoch": 0.99,
"mmlu_eval_accuracy": 0.4617285223167345,
"mmlu_eval_accuracy_abstract_algebra": 0.45454545454545453,
"mmlu_eval_accuracy_anatomy": 0.5714285714285714,
"mmlu_eval_accuracy_astronomy": 0.5,
"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": 0.2727272727272727,
"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": 0.38461538461538464,
"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": 0.4375,
"mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
"mmlu_eval_accuracy_high_school_computer_science": 0.4444444444444444,
"mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
"mmlu_eval_accuracy_high_school_geography": 0.7272727272727273,
"mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_macroeconomics": 0.3488372093023256,
"mmlu_eval_accuracy_high_school_mathematics": 0.10344827586206896,
"mmlu_eval_accuracy_high_school_microeconomics": 0.5,
"mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
"mmlu_eval_accuracy_high_school_psychology": 0.7,
"mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
"mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
"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": 0.36363636363636365,
"mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
"mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
"mmlu_eval_accuracy_management": 0.7272727272727273,
"mmlu_eval_accuracy_marketing": 0.72,
"mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
"mmlu_eval_accuracy_miscellaneous": 0.686046511627907,
"mmlu_eval_accuracy_moral_disputes": 0.5,
"mmlu_eval_accuracy_moral_scenarios": 0.24,
"mmlu_eval_accuracy_nutrition": 0.5454545454545454,
"mmlu_eval_accuracy_philosophy": 0.47058823529411764,
"mmlu_eval_accuracy_prehistory": 0.4857142857142857,
"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": 0.42028985507246375,
"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": 0.3333333333333333,
"mmlu_eval_accuracy_world_religions": 0.7368421052631579,
"mmlu_loss": 1.2059359818152287,
"step": 2800
},
{
"epoch": 0.99,
"learning_rate": 0.0002,
"loss": 0.7341,
"step": 2810
},
{
"epoch": 0.99,
"learning_rate": 0.0002,
"loss": 0.7175,
"step": 2820
},
{
"epoch": 1.0,
"learning_rate": 0.0002,
"loss": 0.6706,
"step": 2830
},
{
"epoch": 1.0,
"learning_rate": 0.0002,
"loss": 0.6273,
"step": 2840
},
{
"epoch": 1.01,
"learning_rate": 0.0002,
"loss": 0.6064,
"step": 2850
},
{
"epoch": 1.01,
"learning_rate": 0.0002,
"loss": 0.6719,
"step": 2860
},
{
"epoch": 1.01,
"learning_rate": 0.0002,
"loss": 0.6426,
"step": 2870
},
{
"epoch": 1.02,
"learning_rate": 0.0002,
"loss": 0.6111,
"step": 2880
},
{
"epoch": 1.02,
"learning_rate": 0.0002,
"loss": 0.6084,
"step": 2890
},
{
"epoch": 1.02,
"learning_rate": 0.0002,
"loss": 0.6414,
"step": 2900
},
{
"epoch": 1.03,
"learning_rate": 0.0002,
"loss": 0.6305,
"step": 2910
},
{
"epoch": 1.03,
"learning_rate": 0.0002,
"loss": 0.6568,
"step": 2920
},
{
"epoch": 1.03,
"learning_rate": 0.0002,
"loss": 0.6456,
"step": 2930
},
{
"epoch": 1.04,
"learning_rate": 0.0002,
"loss": 0.6124,
"step": 2940
},
{
"epoch": 1.04,
"learning_rate": 0.0002,
"loss": 0.6381,
"step": 2950
},
{
"epoch": 1.04,
"learning_rate": 0.0002,
"loss": 0.6184,
"step": 2960
},
{
"epoch": 1.05,
"learning_rate": 0.0002,
"loss": 0.588,
"step": 2970
},
{
"epoch": 1.05,
"learning_rate": 0.0002,
"loss": 0.6697,
"step": 2980
},
{
"epoch": 1.05,
"learning_rate": 0.0002,
"loss": 0.6403,
"step": 2990
},
{
"epoch": 1.06,
"learning_rate": 0.0002,
"loss": 0.6339,
"step": 3000
},
{
"epoch": 1.06,
"eval_loss": 0.7678287625312805,
"eval_runtime": 184.2482,
"eval_samples_per_second": 5.427,
"eval_steps_per_second": 2.714,
"step": 3000
},
{
"epoch": 1.06,
"mmlu_eval_accuracy": 0.46810410139947695,
"mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
"mmlu_eval_accuracy_anatomy": 0.5,
"mmlu_eval_accuracy_astronomy": 0.5,
"mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
"mmlu_eval_accuracy_clinical_knowledge": 0.41379310344827586,
"mmlu_eval_accuracy_college_biology": 0.375,
"mmlu_eval_accuracy_college_chemistry": 0.25,
"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": 0.2727272727272727,
"mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
"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": 0.5,
"mmlu_eval_accuracy_high_school_biology": 0.40625,
"mmlu_eval_accuracy_high_school_chemistry": 0.36363636363636365,
"mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
"mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
"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": 0.46153846153846156,
"mmlu_eval_accuracy_high_school_physics": 0.35294117647058826,
"mmlu_eval_accuracy_high_school_psychology": 0.6833333333333333,
"mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
"mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
"mmlu_eval_accuracy_high_school_world_history": 0.5769230769230769,
"mmlu_eval_accuracy_human_aging": 0.6521739130434783,
"mmlu_eval_accuracy_human_sexuality": 0.5833333333333334,
"mmlu_eval_accuracy_international_law": 0.6923076923076923,
"mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
"mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
"mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
"mmlu_eval_accuracy_management": 0.7272727272727273,
"mmlu_eval_accuracy_marketing": 0.72,
"mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
"mmlu_eval_accuracy_miscellaneous": 0.686046511627907,
"mmlu_eval_accuracy_moral_disputes": 0.5,
"mmlu_eval_accuracy_moral_scenarios": 0.24,
"mmlu_eval_accuracy_nutrition": 0.5757575757575758,
"mmlu_eval_accuracy_philosophy": 0.4411764705882353,
"mmlu_eval_accuracy_prehistory": 0.45714285714285713,
"mmlu_eval_accuracy_professional_accounting": 0.3548387096774194,
"mmlu_eval_accuracy_professional_law": 0.34705882352941175,
"mmlu_eval_accuracy_professional_medicine": 0.45161290322580644,
"mmlu_eval_accuracy_professional_psychology": 0.42028985507246375,
"mmlu_eval_accuracy_public_relations": 0.4166666666666667,
"mmlu_eval_accuracy_security_studies": 0.5555555555555556,
"mmlu_eval_accuracy_sociology": 0.6818181818181818,
"mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
"mmlu_eval_accuracy_virology": 0.5555555555555556,
"mmlu_eval_accuracy_world_religions": 0.7368421052631579,
"mmlu_loss": 1.0877072031830994,
"step": 3000
},
{
"epoch": 1.06,
"learning_rate": 0.0002,
"loss": 0.6124,
"step": 3010
},
{
"epoch": 1.07,
"learning_rate": 0.0002,
"loss": 0.5688,
"step": 3020
},
{
"epoch": 1.07,
"learning_rate": 0.0002,
"loss": 0.5921,
"step": 3030
},
{
"epoch": 1.07,
"learning_rate": 0.0002,
"loss": 0.6182,
"step": 3040
},
{
"epoch": 1.08,
"learning_rate": 0.0002,
"loss": 0.6351,
"step": 3050
},
{
"epoch": 1.08,
"learning_rate": 0.0002,
"loss": 0.672,
"step": 3060
},
{
"epoch": 1.08,
"learning_rate": 0.0002,
"loss": 0.6648,
"step": 3070
},
{
"epoch": 1.09,
"learning_rate": 0.0002,
"loss": 0.6858,
"step": 3080
},
{
"epoch": 1.09,
"learning_rate": 0.0002,
"loss": 0.6367,
"step": 3090
},
{
"epoch": 1.09,
"learning_rate": 0.0002,
"loss": 0.5801,
"step": 3100
},
{
"epoch": 1.1,
"learning_rate": 0.0002,
"loss": 0.6313,
"step": 3110
},
{
"epoch": 1.1,
"learning_rate": 0.0002,
"loss": 0.614,
"step": 3120
},
{
"epoch": 1.1,
"learning_rate": 0.0002,
"loss": 0.6164,
"step": 3130
},
{
"epoch": 1.11,
"learning_rate": 0.0002,
"loss": 0.6137,
"step": 3140
},
{
"epoch": 1.11,
"learning_rate": 0.0002,
"loss": 0.6205,
"step": 3150
},
{
"epoch": 1.11,
"learning_rate": 0.0002,
"loss": 0.6495,
"step": 3160
},
{
"epoch": 1.12,
"learning_rate": 0.0002,
"loss": 0.6411,
"step": 3170
},
{
"epoch": 1.12,
"learning_rate": 0.0002,
"loss": 0.6338,
"step": 3180
},
{
"epoch": 1.13,
"learning_rate": 0.0002,
"loss": 0.6278,
"step": 3190
},
{
"epoch": 1.13,
"learning_rate": 0.0002,
"loss": 0.6291,
"step": 3200
},
{
"epoch": 1.13,
"eval_loss": 0.769086480140686,
"eval_runtime": 184.5863,
"eval_samples_per_second": 5.418,
"eval_steps_per_second": 2.709,
"step": 3200
},
{
"epoch": 1.13,
"mmlu_eval_accuracy": 0.46426909704043023,
"mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
"mmlu_eval_accuracy_anatomy": 0.5,
"mmlu_eval_accuracy_astronomy": 0.5625,
"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": 0.45454545454545453,
"mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
"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": 0.4230769230769231,
"mmlu_eval_accuracy_econometrics": 0.16666666666666666,
"mmlu_eval_accuracy_electrical_engineering": 0.3125,
"mmlu_eval_accuracy_elementary_mathematics": 0.36585365853658536,
"mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
"mmlu_eval_accuracy_global_facts": 0.4,
"mmlu_eval_accuracy_high_school_biology": 0.40625,
"mmlu_eval_accuracy_high_school_chemistry": 0.36363636363636365,
"mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
"mmlu_eval_accuracy_high_school_european_history": 0.5,
"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": 0.34782608695652173,
"mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
"mmlu_eval_accuracy_high_school_world_history": 0.5384615384615384,
"mmlu_eval_accuracy_human_aging": 0.6086956521739131,
"mmlu_eval_accuracy_human_sexuality": 0.5,
"mmlu_eval_accuracy_international_law": 0.6923076923076923,
"mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
"mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
"mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
"mmlu_eval_accuracy_management": 0.7272727272727273,
"mmlu_eval_accuracy_marketing": 0.72,
"mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
"mmlu_eval_accuracy_miscellaneous": 0.6744186046511628,
"mmlu_eval_accuracy_moral_disputes": 0.5263157894736842,
"mmlu_eval_accuracy_moral_scenarios": 0.24,
"mmlu_eval_accuracy_nutrition": 0.5454545454545454,
"mmlu_eval_accuracy_philosophy": 0.5,
"mmlu_eval_accuracy_prehistory": 0.5142857142857142,
"mmlu_eval_accuracy_professional_accounting": 0.3225806451612903,
"mmlu_eval_accuracy_professional_law": 0.3235294117647059,
"mmlu_eval_accuracy_professional_medicine": 0.3870967741935484,
"mmlu_eval_accuracy_professional_psychology": 0.42028985507246375,
"mmlu_eval_accuracy_public_relations": 0.4166666666666667,
"mmlu_eval_accuracy_security_studies": 0.5925925925925926,
"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": 1.0945545882764747,
"step": 3200
},
{
"epoch": 1.13,
"learning_rate": 0.0002,
"loss": 0.5948,
"step": 3210
},
{
"epoch": 1.14,
"learning_rate": 0.0002,
"loss": 0.6622,
"step": 3220
},
{
"epoch": 1.14,
"learning_rate": 0.0002,
"loss": 0.6265,
"step": 3230
},
{
"epoch": 1.14,
"learning_rate": 0.0002,
"loss": 0.6154,
"step": 3240
},
{
"epoch": 1.15,
"learning_rate": 0.0002,
"loss": 0.5703,
"step": 3250
},
{
"epoch": 1.15,
"learning_rate": 0.0002,
"loss": 0.6418,
"step": 3260
},
{
"epoch": 1.15,
"learning_rate": 0.0002,
"loss": 0.6197,
"step": 3270
},
{
"epoch": 1.16,
"learning_rate": 0.0002,
"loss": 0.6295,
"step": 3280
},
{
"epoch": 1.16,
"learning_rate": 0.0002,
"loss": 0.6537,
"step": 3290
},
{
"epoch": 1.16,
"learning_rate": 0.0002,
"loss": 0.5913,
"step": 3300
},
{
"epoch": 1.17,
"learning_rate": 0.0002,
"loss": 0.6146,
"step": 3310
},
{
"epoch": 1.17,
"learning_rate": 0.0002,
"loss": 0.6304,
"step": 3320
},
{
"epoch": 1.17,
"learning_rate": 0.0002,
"loss": 0.6601,
"step": 3330
},
{
"epoch": 1.18,
"learning_rate": 0.0002,
"loss": 0.5797,
"step": 3340
},
{
"epoch": 1.18,
"learning_rate": 0.0002,
"loss": 0.6143,
"step": 3350
},
{
"epoch": 1.19,
"learning_rate": 0.0002,
"loss": 0.674,
"step": 3360
},
{
"epoch": 1.19,
"learning_rate": 0.0002,
"loss": 0.6489,
"step": 3370
},
{
"epoch": 1.19,
"learning_rate": 0.0002,
"loss": 0.6867,
"step": 3380
},
{
"epoch": 1.2,
"learning_rate": 0.0002,
"loss": 0.6091,
"step": 3390
},
{
"epoch": 1.2,
"learning_rate": 0.0002,
"loss": 0.6734,
"step": 3400
},
{
"epoch": 1.2,
"eval_loss": 0.7711524367332458,
"eval_runtime": 185.1721,
"eval_samples_per_second": 5.4,
"eval_steps_per_second": 2.7,
"step": 3400
},
{
"epoch": 1.2,
"mmlu_eval_accuracy": 0.462289893215491,
"mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
"mmlu_eval_accuracy_anatomy": 0.5,
"mmlu_eval_accuracy_astronomy": 0.5,
"mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
"mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655,
"mmlu_eval_accuracy_college_biology": 0.3125,
"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": 0.4230769230769231,
"mmlu_eval_accuracy_econometrics": 0.08333333333333333,
"mmlu_eval_accuracy_electrical_engineering": 0.4375,
"mmlu_eval_accuracy_elementary_mathematics": 0.2926829268292683,
"mmlu_eval_accuracy_formal_logic": 0.35714285714285715,
"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": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_macroeconomics": 0.27906976744186046,
"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": 0.7,
"mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
"mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
"mmlu_eval_accuracy_high_school_world_history": 0.5384615384615384,
"mmlu_eval_accuracy_human_aging": 0.6521739130434783,
"mmlu_eval_accuracy_human_sexuality": 0.5833333333333334,
"mmlu_eval_accuracy_international_law": 0.6923076923076923,
"mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
"mmlu_eval_accuracy_logical_fallacies": 0.5,
"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": 0.6744186046511628,
"mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
"mmlu_eval_accuracy_moral_scenarios": 0.24,
"mmlu_eval_accuracy_nutrition": 0.5757575757575758,
"mmlu_eval_accuracy_philosophy": 0.5294117647058824,
"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": 0.42028985507246375,
"mmlu_eval_accuracy_public_relations": 0.5,
"mmlu_eval_accuracy_security_studies": 0.5555555555555556,
"mmlu_eval_accuracy_sociology": 0.7272727272727273,
"mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
"mmlu_eval_accuracy_virology": 0.5,
"mmlu_eval_accuracy_world_religions": 0.7368421052631579,
"mmlu_loss": 1.2021908294944477,
"step": 3400
}
],
"max_steps": 5000,
"num_train_epochs": 2,
"total_flos": 7.858095077549261e+17,
"trial_name": null,
"trial_params": null
}