{ "best_metric": 0.7248261570930481, "best_model_checkpoint": "./output_v2/7b_cluster011_Nous-Hermes-llama-2-7b_partitioned_v3_standardized_011/checkpoint-800", "epoch": 3.2388663967611335, "global_step": 1400, "is_hyper_param_search": false, "is_local_process_zero": true, "is_world_process_zero": true, "log_history": [ { "epoch": 0.02, "learning_rate": 0.0002, "loss": 0.7957, "step": 10 }, { "epoch": 0.05, "learning_rate": 0.0002, "loss": 0.718, "step": 20 }, { "epoch": 0.07, "learning_rate": 0.0002, "loss": 0.73, "step": 30 }, { "epoch": 0.09, "learning_rate": 0.0002, "loss": 0.7826, "step": 40 }, { "epoch": 0.12, "learning_rate": 0.0002, "loss": 0.7013, "step": 50 }, { "epoch": 0.14, "learning_rate": 0.0002, "loss": 0.7353, "step": 60 }, { "epoch": 0.16, "learning_rate": 0.0002, "loss": 0.6666, "step": 70 }, { "epoch": 0.19, "learning_rate": 0.0002, "loss": 0.7649, "step": 80 }, { "epoch": 0.21, "learning_rate": 0.0002, "loss": 0.7018, "step": 90 }, { "epoch": 0.23, "learning_rate": 0.0002, "loss": 0.7173, "step": 100 }, { "epoch": 0.25, "learning_rate": 0.0002, "loss": 0.7857, "step": 110 }, { "epoch": 0.28, "learning_rate": 0.0002, "loss": 0.7154, "step": 120 }, { "epoch": 0.3, "learning_rate": 0.0002, "loss": 0.7485, "step": 130 }, { "epoch": 0.32, "learning_rate": 0.0002, "loss": 0.7114, "step": 140 }, { "epoch": 0.35, "learning_rate": 0.0002, "loss": 0.7333, "step": 150 }, { "epoch": 0.37, "learning_rate": 0.0002, "loss": 0.6549, "step": 160 }, { "epoch": 0.39, "learning_rate": 0.0002, "loss": 0.6765, "step": 170 }, { "epoch": 0.42, "learning_rate": 0.0002, "loss": 0.677, "step": 180 }, { "epoch": 0.44, "learning_rate": 0.0002, "loss": 0.6763, "step": 190 }, { "epoch": 0.46, "learning_rate": 0.0002, "loss": 0.6638, "step": 200 }, { "epoch": 0.46, "eval_loss": 0.7327473163604736, "eval_runtime": 246.3779, "eval_samples_per_second": 4.059, "eval_steps_per_second": 2.029, "step": 200 }, { "epoch": 0.46, "mmlu_eval_accuracy": 0.4592376175825003, "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727, "mmlu_eval_accuracy_anatomy": 0.5714285714285714, "mmlu_eval_accuracy_astronomy": 0.375, "mmlu_eval_accuracy_business_ethics": 0.5454545454545454, "mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655, "mmlu_eval_accuracy_college_biology": 0.4375, "mmlu_eval_accuracy_college_chemistry": 0.125, "mmlu_eval_accuracy_college_computer_science": 0.45454545454545453, "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": 0.36363636363636365, "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": 0.2857142857142857, "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": 0.7272727272727273, "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": 0.7333333333333333, "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087, "mmlu_eval_accuracy_high_school_us_history": 0.6818181818181818, "mmlu_eval_accuracy_high_school_world_history": 0.5384615384615384, "mmlu_eval_accuracy_human_aging": 0.6956521739130435, "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333, "mmlu_eval_accuracy_international_law": 0.6923076923076923, "mmlu_eval_accuracy_jurisprudence": 0.5454545454545454, "mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556, "mmlu_eval_accuracy_machine_learning": 0.2727272727272727, "mmlu_eval_accuracy_management": 0.6363636363636364, "mmlu_eval_accuracy_marketing": 0.72, "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273, "mmlu_eval_accuracy_miscellaneous": 0.7093023255813954, "mmlu_eval_accuracy_moral_disputes": 0.39473684210526316, "mmlu_eval_accuracy_moral_scenarios": 0.24, "mmlu_eval_accuracy_nutrition": 0.5757575757575758, "mmlu_eval_accuracy_philosophy": 0.38235294117647056, "mmlu_eval_accuracy_prehistory": 0.45714285714285713, "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613, "mmlu_eval_accuracy_professional_law": 0.34705882352941175, "mmlu_eval_accuracy_professional_medicine": 0.41935483870967744, "mmlu_eval_accuracy_professional_psychology": 0.391304347826087, "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": 0.45454545454545453, "mmlu_eval_accuracy_virology": 0.4444444444444444, "mmlu_eval_accuracy_world_religions": 0.7368421052631579, "mmlu_loss": 1.173365458184683, "step": 200 }, { "epoch": 0.49, "learning_rate": 0.0002, "loss": 0.6849, "step": 210 }, { "epoch": 0.51, "learning_rate": 0.0002, "loss": 0.7275, "step": 220 }, { "epoch": 0.53, "learning_rate": 0.0002, "loss": 0.6976, "step": 230 }, { "epoch": 0.56, "learning_rate": 0.0002, "loss": 0.6896, "step": 240 }, { "epoch": 0.58, "learning_rate": 0.0002, "loss": 0.6831, "step": 250 }, { "epoch": 0.6, "learning_rate": 0.0002, "loss": 0.8049, "step": 260 }, { "epoch": 0.62, "learning_rate": 0.0002, "loss": 0.6878, "step": 270 }, { "epoch": 0.65, "learning_rate": 0.0002, "loss": 0.6679, "step": 280 }, { "epoch": 0.67, "learning_rate": 0.0002, "loss": 0.6808, "step": 290 }, { "epoch": 0.69, "learning_rate": 0.0002, "loss": 0.7648, "step": 300 }, { "epoch": 0.72, "learning_rate": 0.0002, "loss": 0.7605, "step": 310 }, { "epoch": 0.74, "learning_rate": 0.0002, "loss": 0.7504, "step": 320 }, { "epoch": 0.76, "learning_rate": 0.0002, "loss": 0.7853, "step": 330 }, { "epoch": 0.79, "learning_rate": 0.0002, "loss": 0.7272, "step": 340 }, { "epoch": 0.81, "learning_rate": 0.0002, "loss": 0.6934, "step": 350 }, { "epoch": 0.83, "learning_rate": 0.0002, "loss": 0.7053, "step": 360 }, { "epoch": 0.86, "learning_rate": 0.0002, "loss": 0.7487, "step": 370 }, { "epoch": 0.88, "learning_rate": 0.0002, "loss": 0.668, "step": 380 }, { "epoch": 0.9, "learning_rate": 0.0002, "loss": 0.6899, "step": 390 }, { "epoch": 0.93, "learning_rate": 0.0002, "loss": 0.684, "step": 400 }, { "epoch": 0.93, "eval_loss": 0.7251922488212585, "eval_runtime": 246.5381, "eval_samples_per_second": 4.056, "eval_steps_per_second": 2.028, "step": 400 }, { "epoch": 0.93, "mmlu_eval_accuracy": 0.46184696708834644, "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182, "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": 0.45454545454545453, "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": 0.38461538461538464, "mmlu_eval_accuracy_econometrics": 0.16666666666666666, "mmlu_eval_accuracy_electrical_engineering": 0.5, "mmlu_eval_accuracy_elementary_mathematics": 0.36585365853658536, "mmlu_eval_accuracy_formal_logic": 0.35714285714285715, "mmlu_eval_accuracy_global_facts": 0.5, "mmlu_eval_accuracy_high_school_biology": 0.34375, "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091, "mmlu_eval_accuracy_high_school_computer_science": 0.6666666666666666, "mmlu_eval_accuracy_high_school_european_history": 0.7222222222222222, "mmlu_eval_accuracy_high_school_geography": 0.8181818181818182, "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191, "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723, "mmlu_eval_accuracy_high_school_mathematics": 0.13793103448275862, "mmlu_eval_accuracy_high_school_microeconomics": 0.4230769230769231, "mmlu_eval_accuracy_high_school_physics": 0.35294117647058826, "mmlu_eval_accuracy_high_school_psychology": 0.75, "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654, "mmlu_eval_accuracy_high_school_us_history": 0.6818181818181818, "mmlu_eval_accuracy_high_school_world_history": 0.5769230769230769, "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": 0.18181818181818182, "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": 0.4411764705882353, "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": 0.45161290322580644, "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": 0.6363636363636364, "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454, "mmlu_eval_accuracy_virology": 0.3888888888888889, "mmlu_eval_accuracy_world_religions": 0.7368421052631579, "mmlu_loss": 1.1016935974982016, "step": 400 }, { "epoch": 0.95, "learning_rate": 0.0002, "loss": 0.7535, "step": 410 }, { "epoch": 0.97, "learning_rate": 0.0002, "loss": 0.707, "step": 420 }, { "epoch": 0.99, "learning_rate": 0.0002, "loss": 0.7077, "step": 430 }, { "epoch": 1.02, "learning_rate": 0.0002, "loss": 0.6389, "step": 440 }, { "epoch": 1.04, "learning_rate": 0.0002, "loss": 0.6701, "step": 450 }, { "epoch": 1.06, "learning_rate": 0.0002, "loss": 0.6462, "step": 460 }, { "epoch": 1.09, "learning_rate": 0.0002, "loss": 0.6421, "step": 470 }, { "epoch": 1.11, "learning_rate": 0.0002, "loss": 0.6822, "step": 480 }, { "epoch": 1.13, "learning_rate": 0.0002, "loss": 0.5916, "step": 490 }, { "epoch": 1.16, "learning_rate": 0.0002, "loss": 0.7141, "step": 500 }, { "epoch": 1.18, "learning_rate": 0.0002, "loss": 0.679, "step": 510 }, { "epoch": 1.2, "learning_rate": 0.0002, "loss": 0.5723, "step": 520 }, { "epoch": 1.23, "learning_rate": 0.0002, "loss": 0.6451, "step": 530 }, { "epoch": 1.25, "learning_rate": 0.0002, "loss": 0.6802, "step": 540 }, { "epoch": 1.27, "learning_rate": 0.0002, "loss": 0.5868, "step": 550 }, { "epoch": 1.3, "learning_rate": 0.0002, "loss": 0.6386, "step": 560 }, { "epoch": 1.32, "learning_rate": 0.0002, "loss": 0.5967, "step": 570 }, { "epoch": 1.34, "learning_rate": 0.0002, "loss": 0.618, "step": 580 }, { "epoch": 1.36, "learning_rate": 0.0002, "loss": 0.6294, "step": 590 }, { "epoch": 1.39, "learning_rate": 0.0002, "loss": 0.6417, "step": 600 }, { "epoch": 1.39, "eval_loss": 0.7272388935089111, "eval_runtime": 247.55, "eval_samples_per_second": 4.04, "eval_steps_per_second": 2.02, "step": 600 }, { "epoch": 1.39, "mmlu_eval_accuracy": 0.4580576219014606, "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": 0.5, "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": 0.3181818181818182, "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": 0.2857142857142857, "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": 0.7222222222222222, "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727, "mmlu_eval_accuracy_high_school_government_and_politics": 0.5238095238095238, "mmlu_eval_accuracy_high_school_macroeconomics": 0.3488372093023256, "mmlu_eval_accuracy_high_school_mathematics": 0.13793103448275862, "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": 0.2608695652173913, "mmlu_eval_accuracy_high_school_us_history": 0.6818181818181818, "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": 0.7692307692307693, "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": 0.72, "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": 0.23, "mmlu_eval_accuracy_nutrition": 0.5757575757575758, "mmlu_eval_accuracy_philosophy": 0.4117647058823529, "mmlu_eval_accuracy_prehistory": 0.4857142857142857, "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613, "mmlu_eval_accuracy_professional_law": 0.3411764705882353, "mmlu_eval_accuracy_professional_medicine": 0.4838709677419355, "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": 0.5454545454545454, "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454, "mmlu_eval_accuracy_virology": 0.3888888888888889, "mmlu_eval_accuracy_world_religions": 0.7368421052631579, "mmlu_loss": 1.069228487308125, "step": 600 }, { "epoch": 1.41, "learning_rate": 0.0002, "loss": 0.6904, "step": 610 }, { "epoch": 1.43, "learning_rate": 0.0002, "loss": 0.6646, "step": 620 }, { "epoch": 1.46, "learning_rate": 0.0002, "loss": 0.6827, "step": 630 }, { "epoch": 1.48, "learning_rate": 0.0002, "loss": 0.6825, "step": 640 }, { "epoch": 1.5, "learning_rate": 0.0002, "loss": 0.6406, "step": 650 }, { "epoch": 1.53, "learning_rate": 0.0002, "loss": 0.6767, "step": 660 }, { "epoch": 1.55, "learning_rate": 0.0002, "loss": 0.6222, "step": 670 }, { "epoch": 1.57, "learning_rate": 0.0002, "loss": 0.5656, "step": 680 }, { "epoch": 1.6, "learning_rate": 0.0002, "loss": 0.6281, "step": 690 }, { "epoch": 1.62, "learning_rate": 0.0002, "loss": 0.6449, "step": 700 }, { "epoch": 1.64, "learning_rate": 0.0002, "loss": 0.6087, "step": 710 }, { "epoch": 1.67, "learning_rate": 0.0002, "loss": 0.6179, "step": 720 }, { "epoch": 1.69, "learning_rate": 0.0002, "loss": 0.596, "step": 730 }, { "epoch": 1.71, "learning_rate": 0.0002, "loss": 0.6577, "step": 740 }, { "epoch": 1.74, "learning_rate": 0.0002, "loss": 0.65, "step": 750 }, { "epoch": 1.76, "learning_rate": 0.0002, "loss": 0.5936, "step": 760 }, { "epoch": 1.78, "learning_rate": 0.0002, "loss": 0.65, "step": 770 }, { "epoch": 1.8, "learning_rate": 0.0002, "loss": 0.5787, "step": 780 }, { "epoch": 1.83, "learning_rate": 0.0002, "loss": 0.6082, "step": 790 }, { "epoch": 1.85, "learning_rate": 0.0002, "loss": 0.6129, "step": 800 }, { "epoch": 1.85, "eval_loss": 0.7248261570930481, "eval_runtime": 246.8878, "eval_samples_per_second": 4.05, "eval_steps_per_second": 2.025, "step": 800 }, { "epoch": 1.85, "mmlu_eval_accuracy": 0.4610550473708825, "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": 0.5, "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": 0.3181818181818182, "mmlu_eval_accuracy_college_physics": 0.45454545454545453, "mmlu_eval_accuracy_computer_security": 0.18181818181818182, "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464, "mmlu_eval_accuracy_econometrics": 0.16666666666666666, "mmlu_eval_accuracy_electrical_engineering": 0.4375, "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637, "mmlu_eval_accuracy_formal_logic": 0.2857142857142857, "mmlu_eval_accuracy_global_facts": 0.5, "mmlu_eval_accuracy_high_school_biology": 0.375, "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091, "mmlu_eval_accuracy_high_school_computer_science": 0.6666666666666666, "mmlu_eval_accuracy_high_school_european_history": 0.7222222222222222, "mmlu_eval_accuracy_high_school_geography": 0.7272727272727273, "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714, "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723, "mmlu_eval_accuracy_high_school_mathematics": 0.1724137931034483, "mmlu_eval_accuracy_high_school_microeconomics": 0.5, "mmlu_eval_accuracy_high_school_physics": 0.35294117647058826, "mmlu_eval_accuracy_high_school_psychology": 0.6833333333333333, "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654, "mmlu_eval_accuracy_high_school_us_history": 0.6818181818181818, "mmlu_eval_accuracy_high_school_world_history": 0.6153846153846154, "mmlu_eval_accuracy_human_aging": 0.6521739130434783, "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": 0.45454545454545453, "mmlu_eval_accuracy_marketing": 0.76, "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273, "mmlu_eval_accuracy_miscellaneous": 0.6744186046511628, "mmlu_eval_accuracy_moral_disputes": 0.42105263157894735, "mmlu_eval_accuracy_moral_scenarios": 0.24, "mmlu_eval_accuracy_nutrition": 0.5151515151515151, "mmlu_eval_accuracy_philosophy": 0.4117647058823529, "mmlu_eval_accuracy_prehistory": 0.42857142857142855, "mmlu_eval_accuracy_professional_accounting": 0.3225806451612903, "mmlu_eval_accuracy_professional_law": 0.3411764705882353, "mmlu_eval_accuracy_professional_medicine": 0.4838709677419355, "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": 0.5454545454545454, "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454, "mmlu_eval_accuracy_virology": 0.3888888888888889, "mmlu_eval_accuracy_world_religions": 0.7368421052631579, "mmlu_loss": 1.0681800356538427, "step": 800 }, { "epoch": 1.87, "learning_rate": 0.0002, "loss": 0.6516, "step": 810 }, { "epoch": 1.9, "learning_rate": 0.0002, "loss": 0.6268, "step": 820 }, { "epoch": 1.92, "learning_rate": 0.0002, "loss": 0.6463, "step": 830 }, { "epoch": 1.94, "learning_rate": 0.0002, "loss": 0.6401, "step": 840 }, { "epoch": 1.97, "learning_rate": 0.0002, "loss": 0.6529, "step": 850 }, { "epoch": 1.99, "learning_rate": 0.0002, "loss": 0.6089, "step": 860 }, { "epoch": 2.01, "learning_rate": 0.0002, "loss": 0.5814, "step": 870 }, { "epoch": 2.04, "learning_rate": 0.0002, "loss": 0.4863, "step": 880 }, { "epoch": 2.06, "learning_rate": 0.0002, "loss": 0.5209, "step": 890 }, { "epoch": 2.08, "learning_rate": 0.0002, "loss": 0.4846, "step": 900 }, { "epoch": 2.11, "learning_rate": 0.0002, "loss": 0.5142, "step": 910 }, { "epoch": 2.13, "learning_rate": 0.0002, "loss": 0.5423, "step": 920 }, { "epoch": 2.15, "learning_rate": 0.0002, "loss": 0.5756, "step": 930 }, { "epoch": 2.17, "learning_rate": 0.0002, "loss": 0.5048, "step": 940 }, { "epoch": 2.2, "learning_rate": 0.0002, "loss": 0.5303, "step": 950 }, { "epoch": 2.22, "learning_rate": 0.0002, "loss": 0.5121, "step": 960 }, { "epoch": 2.24, "learning_rate": 0.0002, "loss": 0.574, "step": 970 }, { "epoch": 2.27, "learning_rate": 0.0002, "loss": 0.5207, "step": 980 }, { "epoch": 2.29, "learning_rate": 0.0002, "loss": 0.5412, "step": 990 }, { "epoch": 2.31, "learning_rate": 0.0002, "loss": 0.5303, "step": 1000 }, { "epoch": 2.31, "eval_loss": 0.7593775391578674, "eval_runtime": 246.7377, "eval_samples_per_second": 4.053, "eval_steps_per_second": 2.026, "step": 1000 }, { "epoch": 2.31, "mmlu_eval_accuracy": 0.4569260811160823, "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365, "mmlu_eval_accuracy_anatomy": 0.5, "mmlu_eval_accuracy_astronomy": 0.375, "mmlu_eval_accuracy_business_ethics": 0.5454545454545454, "mmlu_eval_accuracy_clinical_knowledge": 0.3793103448275862, "mmlu_eval_accuracy_college_biology": 0.5, "mmlu_eval_accuracy_college_chemistry": 0.25, "mmlu_eval_accuracy_college_computer_science": 0.5454545454545454, "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182, "mmlu_eval_accuracy_college_medicine": 0.3181818181818182, "mmlu_eval_accuracy_college_physics": 0.45454545454545453, "mmlu_eval_accuracy_computer_security": 0.2727272727272727, "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464, "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": 0.4, "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": 0.6666666666666666, "mmlu_eval_accuracy_high_school_geography": 0.7272727272727273, "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714, "mmlu_eval_accuracy_high_school_macroeconomics": 0.37209302325581395, "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793, "mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156, "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354, "mmlu_eval_accuracy_high_school_psychology": 0.7, "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654, "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364, "mmlu_eval_accuracy_high_school_world_history": 0.5384615384615384, "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": 0.2727272727272727, "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112, "mmlu_eval_accuracy_machine_learning": 0.18181818181818182, "mmlu_eval_accuracy_management": 0.5454545454545454, "mmlu_eval_accuracy_marketing": 0.76, "mmlu_eval_accuracy_medical_genetics": 0.6363636363636364, "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": 0.45714285714285713, "mmlu_eval_accuracy_professional_accounting": 0.3548387096774194, "mmlu_eval_accuracy_professional_law": 0.3588235294117647, "mmlu_eval_accuracy_professional_medicine": 0.4838709677419355, "mmlu_eval_accuracy_professional_psychology": 0.43478260869565216, "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": 0.7368421052631579, "mmlu_loss": 1.3353144975267253, "step": 1000 }, { "epoch": 2.34, "learning_rate": 0.0002, "loss": 0.5821, "step": 1010 }, { "epoch": 2.36, "learning_rate": 0.0002, "loss": 0.5049, "step": 1020 }, { "epoch": 2.38, "learning_rate": 0.0002, "loss": 0.5422, "step": 1030 }, { "epoch": 2.41, "learning_rate": 0.0002, "loss": 0.5449, "step": 1040 }, { "epoch": 2.43, "learning_rate": 0.0002, "loss": 0.5118, "step": 1050 }, { "epoch": 2.45, "learning_rate": 0.0002, "loss": 0.5837, "step": 1060 }, { "epoch": 2.48, "learning_rate": 0.0002, "loss": 0.5563, "step": 1070 }, { "epoch": 2.5, "learning_rate": 0.0002, "loss": 0.5417, "step": 1080 }, { "epoch": 2.52, "learning_rate": 0.0002, "loss": 0.5476, "step": 1090 }, { "epoch": 2.54, "learning_rate": 0.0002, "loss": 0.5308, "step": 1100 }, { "epoch": 2.57, "learning_rate": 0.0002, "loss": 0.5445, "step": 1110 }, { "epoch": 2.59, "learning_rate": 0.0002, "loss": 0.4944, "step": 1120 }, { "epoch": 2.61, "learning_rate": 0.0002, "loss": 0.5082, "step": 1130 }, { "epoch": 2.64, "learning_rate": 0.0002, "loss": 0.5107, "step": 1140 }, { "epoch": 2.66, "learning_rate": 0.0002, "loss": 0.4959, "step": 1150 }, { "epoch": 2.68, "learning_rate": 0.0002, "loss": 0.5311, "step": 1160 }, { "epoch": 2.71, "learning_rate": 0.0002, "loss": 0.5388, "step": 1170 }, { "epoch": 2.73, "learning_rate": 0.0002, "loss": 0.4745, "step": 1180 }, { "epoch": 2.75, "learning_rate": 0.0002, "loss": 0.5232, "step": 1190 }, { "epoch": 2.78, "learning_rate": 0.0002, "loss": 0.5388, "step": 1200 }, { "epoch": 2.78, "eval_loss": 0.7669270634651184, "eval_runtime": 246.0098, "eval_samples_per_second": 4.065, "eval_steps_per_second": 2.032, "step": 1200 }, { "epoch": 2.78, "mmlu_eval_accuracy": 0.4734820857068989, "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": 0.5, "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": 0.6363636363636364, "mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231, "mmlu_eval_accuracy_econometrics": 0.25, "mmlu_eval_accuracy_electrical_engineering": 0.375, "mmlu_eval_accuracy_elementary_mathematics": 0.3170731707317073, "mmlu_eval_accuracy_formal_logic": 0.14285714285714285, "mmlu_eval_accuracy_global_facts": 0.5, "mmlu_eval_accuracy_high_school_biology": 0.46875, "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091, "mmlu_eval_accuracy_high_school_computer_science": 0.6666666666666666, "mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112, "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727, "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714, "mmlu_eval_accuracy_high_school_macroeconomics": 0.3488372093023256, "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793, "mmlu_eval_accuracy_high_school_microeconomics": 0.5, "mmlu_eval_accuracy_high_school_physics": 0.35294117647058826, "mmlu_eval_accuracy_high_school_psychology": 0.7333333333333333, "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654, "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364, "mmlu_eval_accuracy_high_school_world_history": 0.5769230769230769, "mmlu_eval_accuracy_human_aging": 0.7391304347826086, "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333, "mmlu_eval_accuracy_international_law": 0.7692307692307693, "mmlu_eval_accuracy_jurisprudence": 0.2727272727272727, "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112, "mmlu_eval_accuracy_machine_learning": 0.18181818181818182, "mmlu_eval_accuracy_management": 0.5454545454545454, "mmlu_eval_accuracy_marketing": 0.8, "mmlu_eval_accuracy_medical_genetics": 0.6363636363636364, "mmlu_eval_accuracy_miscellaneous": 0.6395348837209303, "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576, "mmlu_eval_accuracy_moral_scenarios": 0.24, "mmlu_eval_accuracy_nutrition": 0.5454545454545454, "mmlu_eval_accuracy_philosophy": 0.4411764705882353, "mmlu_eval_accuracy_prehistory": 0.5142857142857142, "mmlu_eval_accuracy_professional_accounting": 0.3548387096774194, "mmlu_eval_accuracy_professional_law": 0.3176470588235294, "mmlu_eval_accuracy_professional_medicine": 0.4838709677419355, "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": 0.5909090909090909, "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454, "mmlu_eval_accuracy_virology": 0.5, "mmlu_eval_accuracy_world_religions": 0.7368421052631579, "mmlu_loss": 1.082002373310122, "step": 1200 }, { "epoch": 2.8, "learning_rate": 0.0002, "loss": 0.5243, "step": 1210 }, { "epoch": 2.82, "learning_rate": 0.0002, "loss": 0.5168, "step": 1220 }, { "epoch": 2.85, "learning_rate": 0.0002, "loss": 0.4966, "step": 1230 }, { "epoch": 2.87, "learning_rate": 0.0002, "loss": 0.5869, "step": 1240 }, { "epoch": 2.89, "learning_rate": 0.0002, "loss": 0.5336, "step": 1250 }, { "epoch": 2.91, "learning_rate": 0.0002, "loss": 0.563, "step": 1260 }, { "epoch": 2.94, "learning_rate": 0.0002, "loss": 0.5002, "step": 1270 }, { "epoch": 2.96, "learning_rate": 0.0002, "loss": 0.607, "step": 1280 }, { "epoch": 2.98, "learning_rate": 0.0002, "loss": 0.5458, "step": 1290 }, { "epoch": 3.01, "learning_rate": 0.0002, "loss": 0.5263, "step": 1300 }, { "epoch": 3.03, "learning_rate": 0.0002, "loss": 0.4074, "step": 1310 }, { "epoch": 3.05, "learning_rate": 0.0002, "loss": 0.3737, "step": 1320 }, { "epoch": 3.08, "learning_rate": 0.0002, "loss": 0.3938, "step": 1330 }, { "epoch": 3.1, "learning_rate": 0.0002, "loss": 0.3802, "step": 1340 }, { "epoch": 3.12, "learning_rate": 0.0002, "loss": 0.4216, "step": 1350 }, { "epoch": 3.15, "learning_rate": 0.0002, "loss": 0.4045, "step": 1360 }, { "epoch": 3.17, "learning_rate": 0.0002, "loss": 0.4024, "step": 1370 }, { "epoch": 3.19, "learning_rate": 0.0002, "loss": 0.3943, "step": 1380 }, { "epoch": 3.22, "learning_rate": 0.0002, "loss": 0.3923, "step": 1390 }, { "epoch": 3.24, "learning_rate": 0.0002, "loss": 0.4267, "step": 1400 }, { "epoch": 3.24, "eval_loss": 0.8232849836349487, "eval_runtime": 245.4693, "eval_samples_per_second": 4.074, "eval_steps_per_second": 2.037, "step": 1400 }, { "epoch": 3.24, "mmlu_eval_accuracy": 0.4552997822968728, "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365, "mmlu_eval_accuracy_anatomy": 0.5, "mmlu_eval_accuracy_astronomy": 0.3125, "mmlu_eval_accuracy_business_ethics": 0.5454545454545454, "mmlu_eval_accuracy_clinical_knowledge": 0.4827586206896552, "mmlu_eval_accuracy_college_biology": 0.4375, "mmlu_eval_accuracy_college_chemistry": 0.25, "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365, "mmlu_eval_accuracy_college_mathematics": 0.36363636363636365, "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": 0.4230769230769231, "mmlu_eval_accuracy_econometrics": 0.25, "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": 0.4, "mmlu_eval_accuracy_high_school_biology": 0.46875, "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": 0.7727272727272727, "mmlu_eval_accuracy_high_school_government_and_politics": 0.5238095238095238, "mmlu_eval_accuracy_high_school_macroeconomics": 0.3488372093023256, "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276, "mmlu_eval_accuracy_high_school_microeconomics": 0.5, "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354, "mmlu_eval_accuracy_high_school_psychology": 0.7166666666666667, "mmlu_eval_accuracy_high_school_statistics": 0.2608695652173913, "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364, "mmlu_eval_accuracy_high_school_world_history": 0.6153846153846154, "mmlu_eval_accuracy_human_aging": 0.6521739130434783, "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667, "mmlu_eval_accuracy_international_law": 0.7692307692307693, "mmlu_eval_accuracy_jurisprudence": 0.2727272727272727, "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112, "mmlu_eval_accuracy_machine_learning": 0.18181818181818182, "mmlu_eval_accuracy_management": 0.6363636363636364, "mmlu_eval_accuracy_marketing": 0.76, "mmlu_eval_accuracy_medical_genetics": 0.6363636363636364, "mmlu_eval_accuracy_miscellaneous": 0.6627906976744186, "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576, "mmlu_eval_accuracy_moral_scenarios": 0.21, "mmlu_eval_accuracy_nutrition": 0.5454545454545454, "mmlu_eval_accuracy_philosophy": 0.47058823529411764, "mmlu_eval_accuracy_prehistory": 0.4857142857142857, "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613, "mmlu_eval_accuracy_professional_law": 0.29411764705882354, "mmlu_eval_accuracy_professional_medicine": 0.41935483870967744, "mmlu_eval_accuracy_professional_psychology": 0.34782608695652173, "mmlu_eval_accuracy_public_relations": 0.4166666666666667, "mmlu_eval_accuracy_security_studies": 0.5555555555555556, "mmlu_eval_accuracy_sociology": 0.5454545454545454, "mmlu_eval_accuracy_us_foreign_policy": 0.45454545454545453, "mmlu_eval_accuracy_virology": 0.5555555555555556, "mmlu_eval_accuracy_world_religions": 0.7894736842105263, "mmlu_loss": 1.2433716685416338, "step": 1400 } ], "max_steps": 5000, "num_train_epochs": 12, "total_flos": 3.994598287814492e+17, "trial_name": null, "trial_params": null }