Nous-Hermes-llama-2-7b_7b_cluster031_partitioned_v3_standardized_031
/
checkpoint-200
/trainer_state.json
{ | |
"best_metric": 0.8539559245109558, | |
"best_model_checkpoint": "./output_v2/7b_cluster031_Nous-Hermes-llama-2-7b_partitioned_v3_standardized_031/checkpoint-200", | |
"epoch": 0.13759889920880633, | |
"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": 0.9502, | |
"step": 10 | |
}, | |
{ | |
"epoch": 0.01, | |
"learning_rate": 0.0002, | |
"loss": 0.9426, | |
"step": 20 | |
}, | |
{ | |
"epoch": 0.02, | |
"learning_rate": 0.0002, | |
"loss": 0.9682, | |
"step": 30 | |
}, | |
{ | |
"epoch": 0.03, | |
"learning_rate": 0.0002, | |
"loss": 0.8517, | |
"step": 40 | |
}, | |
{ | |
"epoch": 0.03, | |
"learning_rate": 0.0002, | |
"loss": 0.8944, | |
"step": 50 | |
}, | |
{ | |
"epoch": 0.04, | |
"learning_rate": 0.0002, | |
"loss": 0.8608, | |
"step": 60 | |
}, | |
{ | |
"epoch": 0.05, | |
"learning_rate": 0.0002, | |
"loss": 0.915, | |
"step": 70 | |
}, | |
{ | |
"epoch": 0.06, | |
"learning_rate": 0.0002, | |
"loss": 0.8349, | |
"step": 80 | |
}, | |
{ | |
"epoch": 0.06, | |
"learning_rate": 0.0002, | |
"loss": 0.8912, | |
"step": 90 | |
}, | |
{ | |
"epoch": 0.07, | |
"learning_rate": 0.0002, | |
"loss": 0.876, | |
"step": 100 | |
}, | |
{ | |
"epoch": 0.08, | |
"learning_rate": 0.0002, | |
"loss": 0.8697, | |
"step": 110 | |
}, | |
{ | |
"epoch": 0.08, | |
"learning_rate": 0.0002, | |
"loss": 0.8604, | |
"step": 120 | |
}, | |
{ | |
"epoch": 0.09, | |
"learning_rate": 0.0002, | |
"loss": 0.8654, | |
"step": 130 | |
}, | |
{ | |
"epoch": 0.1, | |
"learning_rate": 0.0002, | |
"loss": 0.8804, | |
"step": 140 | |
}, | |
{ | |
"epoch": 0.1, | |
"learning_rate": 0.0002, | |
"loss": 0.8355, | |
"step": 150 | |
}, | |
{ | |
"epoch": 0.11, | |
"learning_rate": 0.0002, | |
"loss": 0.8704, | |
"step": 160 | |
}, | |
{ | |
"epoch": 0.12, | |
"learning_rate": 0.0002, | |
"loss": 0.8241, | |
"step": 170 | |
}, | |
{ | |
"epoch": 0.12, | |
"learning_rate": 0.0002, | |
"loss": 0.8523, | |
"step": 180 | |
}, | |
{ | |
"epoch": 0.13, | |
"learning_rate": 0.0002, | |
"loss": 0.845, | |
"step": 190 | |
}, | |
{ | |
"epoch": 0.14, | |
"learning_rate": 0.0002, | |
"loss": 0.8681, | |
"step": 200 | |
}, | |
{ | |
"epoch": 0.14, | |
"eval_loss": 0.8539559245109558, | |
"eval_runtime": 189.7934, | |
"eval_samples_per_second": 5.269, | |
"eval_steps_per_second": 2.634, | |
"step": 200 | |
}, | |
{ | |
"epoch": 0.14, | |
"mmlu_eval_accuracy": 0.47295530665862845, | |
"mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727, | |
"mmlu_eval_accuracy_anatomy": 0.5, | |
"mmlu_eval_accuracy_astronomy": 0.375, | |
"mmlu_eval_accuracy_business_ethics": 0.5454545454545454, | |
"mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655, | |
"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": 0.45454545454545453, | |
"mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231, | |
"mmlu_eval_accuracy_econometrics": 0.16666666666666666, | |
"mmlu_eval_accuracy_electrical_engineering": 0.5, | |
"mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637, | |
"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": 0.36363636363636365, | |
"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": 0.20689655172413793, | |
"mmlu_eval_accuracy_high_school_microeconomics": 0.34615384615384615, | |
"mmlu_eval_accuracy_high_school_physics": 0.35294117647058826, | |
"mmlu_eval_accuracy_high_school_psychology": 0.7166666666666667, | |
"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": 0.6956521739130435, | |
"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": 0.76, | |
"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": 0.5757575757575758, | |
"mmlu_eval_accuracy_philosophy": 0.4117647058823529, | |
"mmlu_eval_accuracy_prehistory": 0.42857142857142855, | |
"mmlu_eval_accuracy_professional_accounting": 0.2903225806451613, | |
"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": 0.6666666666666666, | |
"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": 1.2187759077891358, | |
"step": 200 | |
} | |
], | |
"max_steps": 5000, | |
"num_train_epochs": 4, | |
"total_flos": 3.584892315775795e+16, | |
"trial_name": null, | |
"trial_params": null | |
} | |