{ "best_metric": 0.4953967332839966, "best_model_checkpoint": "./output_v2/7b_cluster026_Nous-Hermes-llama-2-7b_partitioned_v3_standardized_026/checkpoint-600", "epoch": 0.6324110671936759, "global_step": 600, "is_hyper_param_search": false, "is_local_process_zero": true, "is_world_process_zero": true, "log_history": [ { "epoch": 0.01, "learning_rate": 0.0002, "loss": 0.723, "step": 10 }, { "epoch": 0.02, "learning_rate": 0.0002, "loss": 0.6175, "step": 20 }, { "epoch": 0.03, "learning_rate": 0.0002, "loss": 0.5857, "step": 30 }, { "epoch": 0.04, "learning_rate": 0.0002, "loss": 0.573, "step": 40 }, { "epoch": 0.05, "learning_rate": 0.0002, "loss": 0.5669, "step": 50 }, { "epoch": 0.06, "learning_rate": 0.0002, "loss": 0.5417, "step": 60 }, { "epoch": 0.07, "learning_rate": 0.0002, "loss": 0.5666, "step": 70 }, { "epoch": 0.08, "learning_rate": 0.0002, "loss": 0.6158, "step": 80 }, { "epoch": 0.09, "learning_rate": 0.0002, "loss": 0.5122, "step": 90 }, { "epoch": 0.11, "learning_rate": 0.0002, "loss": 0.5559, "step": 100 }, { "epoch": 0.12, "learning_rate": 0.0002, "loss": 0.5341, "step": 110 }, { "epoch": 0.13, "learning_rate": 0.0002, "loss": 0.5098, "step": 120 }, { "epoch": 0.14, "learning_rate": 0.0002, "loss": 0.5355, "step": 130 }, { "epoch": 0.15, "learning_rate": 0.0002, "loss": 0.4967, "step": 140 }, { "epoch": 0.16, "learning_rate": 0.0002, "loss": 0.5619, "step": 150 }, { "epoch": 0.17, "learning_rate": 0.0002, "loss": 0.5401, "step": 160 }, { "epoch": 0.18, "learning_rate": 0.0002, "loss": 0.4559, "step": 170 }, { "epoch": 0.19, "learning_rate": 0.0002, "loss": 0.5469, "step": 180 }, { "epoch": 0.2, "learning_rate": 0.0002, "loss": 0.4936, "step": 190 }, { "epoch": 0.21, "learning_rate": 0.0002, "loss": 0.5205, "step": 200 }, { "epoch": 0.21, "eval_loss": 0.526250958442688, "eval_runtime": 127.7705, "eval_samples_per_second": 7.827, "eval_steps_per_second": 3.913, "step": 200 }, { "epoch": 0.21, "mmlu_eval_accuracy": 0.4451746082548338, "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727, "mmlu_eval_accuracy_anatomy": 0.5714285714285714, "mmlu_eval_accuracy_astronomy": 0.5, "mmlu_eval_accuracy_business_ethics": 0.6363636363636364, "mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655, "mmlu_eval_accuracy_college_biology": 0.5, "mmlu_eval_accuracy_college_chemistry": 0.0, "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": 0.2727272727272727, "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": 0.5, "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727, "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191, "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723, "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276, "mmlu_eval_accuracy_high_school_microeconomics": 0.34615384615384615, "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": 0.6818181818181818, "mmlu_eval_accuracy_high_school_world_history": 0.5, "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": 0.18181818181818182, "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": 0.39473684210526316, "mmlu_eval_accuracy_moral_scenarios": 0.23, "mmlu_eval_accuracy_nutrition": 0.5151515151515151, "mmlu_eval_accuracy_philosophy": 0.47058823529411764, "mmlu_eval_accuracy_prehistory": 0.4, "mmlu_eval_accuracy_professional_accounting": 0.25806451612903225, "mmlu_eval_accuracy_professional_law": 0.3235294117647059, "mmlu_eval_accuracy_professional_medicine": 0.41935483870967744, "mmlu_eval_accuracy_professional_psychology": 0.37681159420289856, "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": 1.1821206606554924, "step": 200 }, { "epoch": 0.22, "learning_rate": 0.0002, "loss": 0.528, "step": 210 }, { "epoch": 0.23, "learning_rate": 0.0002, "loss": 0.5451, "step": 220 }, { "epoch": 0.24, "learning_rate": 0.0002, "loss": 0.4991, "step": 230 }, { "epoch": 0.25, "learning_rate": 0.0002, "loss": 0.5335, "step": 240 }, { "epoch": 0.26, "learning_rate": 0.0002, "loss": 0.552, "step": 250 }, { "epoch": 0.27, "learning_rate": 0.0002, "loss": 0.5038, "step": 260 }, { "epoch": 0.28, "learning_rate": 0.0002, "loss": 0.4999, "step": 270 }, { "epoch": 0.3, "learning_rate": 0.0002, "loss": 0.498, "step": 280 }, { "epoch": 0.31, "learning_rate": 0.0002, "loss": 0.5372, "step": 290 }, { "epoch": 0.32, "learning_rate": 0.0002, "loss": 0.5633, "step": 300 }, { "epoch": 0.33, "learning_rate": 0.0002, "loss": 0.555, "step": 310 }, { "epoch": 0.34, "learning_rate": 0.0002, "loss": 0.5152, "step": 320 }, { "epoch": 0.35, "learning_rate": 0.0002, "loss": 0.4703, "step": 330 }, { "epoch": 0.36, "learning_rate": 0.0002, "loss": 0.4987, "step": 340 }, { "epoch": 0.37, "learning_rate": 0.0002, "loss": 0.5223, "step": 350 }, { "epoch": 0.38, "learning_rate": 0.0002, "loss": 0.508, "step": 360 }, { "epoch": 0.39, "learning_rate": 0.0002, "loss": 0.5035, "step": 370 }, { "epoch": 0.4, "learning_rate": 0.0002, "loss": 0.4861, "step": 380 }, { "epoch": 0.41, "learning_rate": 0.0002, "loss": 0.5071, "step": 390 }, { "epoch": 0.42, "learning_rate": 0.0002, "loss": 0.5253, "step": 400 }, { "epoch": 0.42, "eval_loss": 0.5059861540794373, "eval_runtime": 162.7698, "eval_samples_per_second": 6.144, "eval_steps_per_second": 3.072, "step": 400 }, { "epoch": 0.42, "mmlu_eval_accuracy": 0.43943772184310154, "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727, "mmlu_eval_accuracy_anatomy": 0.6428571428571429, "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": 0.4375, "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": 0.36363636363636365, "mmlu_eval_accuracy_college_physics": 0.36363636363636365, "mmlu_eval_accuracy_computer_security": 0.18181818181818182, "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464, "mmlu_eval_accuracy_econometrics": 0.25, "mmlu_eval_accuracy_electrical_engineering": 0.3125, "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637, "mmlu_eval_accuracy_formal_logic": 0.2857142857142857, "mmlu_eval_accuracy_global_facts": 0.3, "mmlu_eval_accuracy_high_school_biology": 0.28125, "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091, "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556, "mmlu_eval_accuracy_high_school_european_history": 0.5, "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727, "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191, "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723, "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724, "mmlu_eval_accuracy_high_school_microeconomics": 0.34615384615384615, "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354, "mmlu_eval_accuracy_high_school_psychology": 0.65, "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654, "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364, "mmlu_eval_accuracy_high_school_world_history": 0.4230769230769231, "mmlu_eval_accuracy_human_aging": 0.6521739130434783, "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": 0.5, "mmlu_eval_accuracy_machine_learning": 0.2727272727272727, "mmlu_eval_accuracy_management": 0.5454545454545454, "mmlu_eval_accuracy_marketing": 0.76, "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273, "mmlu_eval_accuracy_miscellaneous": 0.627906976744186, "mmlu_eval_accuracy_moral_disputes": 0.39473684210526316, "mmlu_eval_accuracy_moral_scenarios": 0.24, "mmlu_eval_accuracy_nutrition": 0.5151515151515151, "mmlu_eval_accuracy_philosophy": 0.5, "mmlu_eval_accuracy_prehistory": 0.45714285714285713, "mmlu_eval_accuracy_professional_accounting": 0.25806451612903225, "mmlu_eval_accuracy_professional_law": 0.3411764705882353, "mmlu_eval_accuracy_professional_medicine": 0.41935483870967744, "mmlu_eval_accuracy_professional_psychology": 0.4057971014492754, "mmlu_eval_accuracy_public_relations": 0.6666666666666666, "mmlu_eval_accuracy_security_studies": 0.48148148148148145, "mmlu_eval_accuracy_sociology": 0.5, "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454, "mmlu_eval_accuracy_virology": 0.5, "mmlu_eval_accuracy_world_religions": 0.7368421052631579, "mmlu_loss": 1.0068739111834344, "step": 400 }, { "epoch": 0.43, "learning_rate": 0.0002, "loss": 0.5145, "step": 410 }, { "epoch": 0.44, "learning_rate": 0.0002, "loss": 0.4798, "step": 420 }, { "epoch": 0.45, "learning_rate": 0.0002, "loss": 0.4728, "step": 430 }, { "epoch": 0.46, "learning_rate": 0.0002, "loss": 0.5151, "step": 440 }, { "epoch": 0.47, "learning_rate": 0.0002, "loss": 0.4784, "step": 450 }, { "epoch": 0.48, "learning_rate": 0.0002, "loss": 0.5029, "step": 460 }, { "epoch": 0.5, "learning_rate": 0.0002, "loss": 0.4603, "step": 470 }, { "epoch": 0.51, "learning_rate": 0.0002, "loss": 0.5177, "step": 480 }, { "epoch": 0.52, "learning_rate": 0.0002, "loss": 0.4676, "step": 490 }, { "epoch": 0.53, "learning_rate": 0.0002, "loss": 0.4294, "step": 500 }, { "epoch": 0.54, "learning_rate": 0.0002, "loss": 0.4927, "step": 510 }, { "epoch": 0.55, "learning_rate": 0.0002, "loss": 0.509, "step": 520 }, { "epoch": 0.56, "learning_rate": 0.0002, "loss": 0.4763, "step": 530 }, { "epoch": 0.57, "learning_rate": 0.0002, "loss": 0.499, "step": 540 }, { "epoch": 0.58, "learning_rate": 0.0002, "loss": 0.4936, "step": 550 }, { "epoch": 0.59, "learning_rate": 0.0002, "loss": 0.5154, "step": 560 }, { "epoch": 0.6, "learning_rate": 0.0002, "loss": 0.5185, "step": 570 }, { "epoch": 0.61, "learning_rate": 0.0002, "loss": 0.4692, "step": 580 }, { "epoch": 0.62, "learning_rate": 0.0002, "loss": 0.4859, "step": 590 }, { "epoch": 0.63, "learning_rate": 0.0002, "loss": 0.4755, "step": 600 }, { "epoch": 0.63, "eval_loss": 0.4953967332839966, "eval_runtime": 127.6509, "eval_samples_per_second": 7.834, "eval_steps_per_second": 3.917, "step": 600 }, { "epoch": 0.63, "mmlu_eval_accuracy": 0.44296636130010114, "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727, "mmlu_eval_accuracy_anatomy": 0.5714285714285714, "mmlu_eval_accuracy_astronomy": 0.4375, "mmlu_eval_accuracy_business_ethics": 0.6363636363636364, "mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655, "mmlu_eval_accuracy_college_biology": 0.4375, "mmlu_eval_accuracy_college_chemistry": 0.0, "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727, "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": 0.45454545454545453, "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": 0.3902439024390244, "mmlu_eval_accuracy_formal_logic": 0.2857142857142857, "mmlu_eval_accuracy_global_facts": 0.3, "mmlu_eval_accuracy_high_school_biology": 0.28125, "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091, "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": 0.5238095238095238, "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723, "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724, "mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156, "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354, "mmlu_eval_accuracy_high_school_psychology": 0.6666666666666666, "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087, "mmlu_eval_accuracy_high_school_us_history": 0.7272727272727273, "mmlu_eval_accuracy_high_school_world_history": 0.4230769230769231, "mmlu_eval_accuracy_human_aging": 0.7391304347826086, "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": 0.5, "mmlu_eval_accuracy_machine_learning": 0.2727272727272727, "mmlu_eval_accuracy_management": 0.5454545454545454, "mmlu_eval_accuracy_marketing": 0.68, "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273, "mmlu_eval_accuracy_miscellaneous": 0.6395348837209303, "mmlu_eval_accuracy_moral_disputes": 0.4473684210526316, "mmlu_eval_accuracy_moral_scenarios": 0.25, "mmlu_eval_accuracy_nutrition": 0.48484848484848486, "mmlu_eval_accuracy_philosophy": 0.4411764705882353, "mmlu_eval_accuracy_prehistory": 0.4857142857142857, "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613, "mmlu_eval_accuracy_professional_law": 0.34705882352941175, "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": 0.48148148148148145, "mmlu_eval_accuracy_sociology": 0.5, "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454, "mmlu_eval_accuracy_virology": 0.5, "mmlu_eval_accuracy_world_religions": 0.6842105263157895, "mmlu_loss": 0.979445159590898, "step": 600 } ], "max_steps": 5000, "num_train_epochs": 6, "total_flos": 8.403180844194202e+16, "trial_name": null, "trial_params": null }