{ "best_metric": 0.6798371076583862, "best_model_checkpoint": "./output_v2/7b_cluster012_Nous-Hermes-llama-2-7b_partitioned_v3_standardized_012/checkpoint-200", "epoch": 0.23161551823972207, "global_step": 200, "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": 0.7418, "step": 10 }, { "epoch": 0.02, "learning_rate": 0.0002, "loss": 0.7269, "step": 20 }, { "epoch": 0.03, "learning_rate": 0.0002, "loss": 0.7061, "step": 30 }, { "epoch": 0.05, "learning_rate": 0.0002, "loss": 0.6809, "step": 40 }, { "epoch": 0.06, "learning_rate": 0.0002, "loss": 0.6742, "step": 50 }, { "epoch": 0.07, "learning_rate": 0.0002, "loss": 0.6789, "step": 60 }, { "epoch": 0.08, "learning_rate": 0.0002, "loss": 0.6628, "step": 70 }, { "epoch": 0.09, "learning_rate": 0.0002, "loss": 0.6995, "step": 80 }, { "epoch": 0.1, "learning_rate": 0.0002, "loss": 0.6774, "step": 90 }, { "epoch": 0.12, "learning_rate": 0.0002, "loss": 0.6716, "step": 100 }, { "epoch": 0.13, "learning_rate": 0.0002, "loss": 0.6628, "step": 110 }, { "epoch": 0.14, "learning_rate": 0.0002, "loss": 0.6696, "step": 120 }, { "epoch": 0.15, "learning_rate": 0.0002, "loss": 0.648, "step": 130 }, { "epoch": 0.16, "learning_rate": 0.0002, "loss": 0.6823, "step": 140 }, { "epoch": 0.17, "learning_rate": 0.0002, "loss": 0.6532, "step": 150 }, { "epoch": 0.19, "learning_rate": 0.0002, "loss": 0.669, "step": 160 }, { "epoch": 0.2, "learning_rate": 0.0002, "loss": 0.6639, "step": 170 }, { "epoch": 0.21, "learning_rate": 0.0002, "loss": 0.6582, "step": 180 }, { "epoch": 0.22, "learning_rate": 0.0002, "loss": 0.6381, "step": 190 }, { "epoch": 0.23, "learning_rate": 0.0002, "loss": 0.6342, "step": 200 }, { "epoch": 0.23, "eval_loss": 0.6798371076583862, "eval_runtime": 220.8775, "eval_samples_per_second": 4.527, "eval_steps_per_second": 2.264, "step": 200 }, { "epoch": 0.23, "mmlu_eval_accuracy": 0.4661323913730994, "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182, "mmlu_eval_accuracy_anatomy": 0.5714285714285714, "mmlu_eval_accuracy_astronomy": 0.5, "mmlu_eval_accuracy_business_ethics": 0.5454545454545454, "mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655, "mmlu_eval_accuracy_college_biology": 0.4375, "mmlu_eval_accuracy_college_chemistry": 0.125, "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365, "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182, "mmlu_eval_accuracy_college_medicine": 0.36363636363636365, "mmlu_eval_accuracy_college_physics": 0.45454545454545453, "mmlu_eval_accuracy_computer_security": 0.36363636363636365, "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464, "mmlu_eval_accuracy_econometrics": 0.16666666666666666, "mmlu_eval_accuracy_electrical_engineering": 0.3125, "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": 0.4090909090909091, "mmlu_eval_accuracy_high_school_computer_science": 0.6666666666666666, "mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112, "mmlu_eval_accuracy_high_school_geography": 0.6818181818181818, "mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666, "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723, "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276, "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": 0.2608695652173913, "mmlu_eval_accuracy_high_school_us_history": 0.7272727272727273, "mmlu_eval_accuracy_high_school_world_history": 0.5769230769230769, "mmlu_eval_accuracy_human_aging": 0.6956521739130435, "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667, "mmlu_eval_accuracy_international_law": 0.7692307692307693, "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365, "mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556, "mmlu_eval_accuracy_machine_learning": 0.2727272727272727, "mmlu_eval_accuracy_management": 0.6363636363636364, "mmlu_eval_accuracy_marketing": 0.76, "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273, "mmlu_eval_accuracy_miscellaneous": 0.6627906976744186, "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": 0.3225806451612903, "mmlu_eval_accuracy_professional_law": 0.35294117647058826, "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": 1.1315238676556718, "step": 200 } ], "max_steps": 5000, "num_train_epochs": 6, "total_flos": 5.082084345131827e+16, "trial_name": null, "trial_params": null }