prateeky2806's picture
Training in progress, step 600
ba0109e
{
"best_metric": 0.6194782853126526,
"best_model_checkpoint": "./output_v2/7b_cluster020_Nous-Hermes-llama-2-7b_partitioned_v3_standardized_020/checkpoint-600",
"epoch": 0.24286581663630843,
"global_step": 600,
"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": 0.6996,
"step": 10
},
{
"epoch": 0.01,
"learning_rate": 0.0002,
"loss": 0.7986,
"step": 20
},
{
"epoch": 0.01,
"learning_rate": 0.0002,
"loss": 0.5936,
"step": 30
},
{
"epoch": 0.02,
"learning_rate": 0.0002,
"loss": 0.6164,
"step": 40
},
{
"epoch": 0.02,
"learning_rate": 0.0002,
"loss": 0.7464,
"step": 50
},
{
"epoch": 0.02,
"learning_rate": 0.0002,
"loss": 0.8856,
"step": 60
},
{
"epoch": 0.03,
"learning_rate": 0.0002,
"loss": 0.6476,
"step": 70
},
{
"epoch": 0.03,
"learning_rate": 0.0002,
"loss": 0.65,
"step": 80
},
{
"epoch": 0.04,
"learning_rate": 0.0002,
"loss": 0.5282,
"step": 90
},
{
"epoch": 0.04,
"learning_rate": 0.0002,
"loss": 0.5787,
"step": 100
},
{
"epoch": 0.04,
"learning_rate": 0.0002,
"loss": 0.6315,
"step": 110
},
{
"epoch": 0.05,
"learning_rate": 0.0002,
"loss": 0.5419,
"step": 120
},
{
"epoch": 0.05,
"learning_rate": 0.0002,
"loss": 0.593,
"step": 130
},
{
"epoch": 0.06,
"learning_rate": 0.0002,
"loss": 0.6773,
"step": 140
},
{
"epoch": 0.06,
"learning_rate": 0.0002,
"loss": 0.5536,
"step": 150
},
{
"epoch": 0.06,
"learning_rate": 0.0002,
"loss": 0.6384,
"step": 160
},
{
"epoch": 0.07,
"learning_rate": 0.0002,
"loss": 0.5736,
"step": 170
},
{
"epoch": 0.07,
"learning_rate": 0.0002,
"loss": 0.6157,
"step": 180
},
{
"epoch": 0.08,
"learning_rate": 0.0002,
"loss": 0.5551,
"step": 190
},
{
"epoch": 0.08,
"learning_rate": 0.0002,
"loss": 0.6446,
"step": 200
},
{
"epoch": 0.08,
"eval_loss": 0.6395586133003235,
"eval_runtime": 94.1614,
"eval_samples_per_second": 10.62,
"eval_steps_per_second": 5.31,
"step": 200
},
{
"epoch": 0.08,
"mmlu_eval_accuracy": 0.4559132721218583,
"mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
"mmlu_eval_accuracy_anatomy": 0.6428571428571429,
"mmlu_eval_accuracy_astronomy": 0.4375,
"mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
"mmlu_eval_accuracy_clinical_knowledge": 0.3793103448275862,
"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": 0.46153846153846156,
"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": 0.3,
"mmlu_eval_accuracy_high_school_biology": 0.3125,
"mmlu_eval_accuracy_high_school_chemistry": 0.36363636363636365,
"mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
"mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
"mmlu_eval_accuracy_high_school_geography": 0.7272727272727273,
"mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
"mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723,
"mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
"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": 0.6956521739130435,
"mmlu_eval_accuracy_human_sexuality": 0.5,
"mmlu_eval_accuracy_international_law": 0.6923076923076923,
"mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
"mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
"mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
"mmlu_eval_accuracy_management": 0.5454545454545454,
"mmlu_eval_accuracy_marketing": 0.72,
"mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
"mmlu_eval_accuracy_miscellaneous": 0.627906976744186,
"mmlu_eval_accuracy_moral_disputes": 0.42105263157894735,
"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": 0.3548387096774194,
"mmlu_eval_accuracy_professional_law": 0.31176470588235294,
"mmlu_eval_accuracy_professional_medicine": 0.3870967741935484,
"mmlu_eval_accuracy_professional_psychology": 0.43478260869565216,
"mmlu_eval_accuracy_public_relations": 0.5,
"mmlu_eval_accuracy_security_studies": 0.4444444444444444,
"mmlu_eval_accuracy_sociology": 0.6363636363636364,
"mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
"mmlu_eval_accuracy_virology": 0.5,
"mmlu_eval_accuracy_world_religions": 0.6842105263157895,
"mmlu_loss": 1.0596903230868493,
"step": 200
},
{
"epoch": 0.09,
"learning_rate": 0.0002,
"loss": 0.7307,
"step": 210
},
{
"epoch": 0.09,
"learning_rate": 0.0002,
"loss": 0.5717,
"step": 220
},
{
"epoch": 0.09,
"learning_rate": 0.0002,
"loss": 0.6836,
"step": 230
},
{
"epoch": 0.1,
"learning_rate": 0.0002,
"loss": 0.5819,
"step": 240
},
{
"epoch": 0.1,
"learning_rate": 0.0002,
"loss": 0.5666,
"step": 250
},
{
"epoch": 0.11,
"learning_rate": 0.0002,
"loss": 0.5266,
"step": 260
},
{
"epoch": 0.11,
"learning_rate": 0.0002,
"loss": 0.5218,
"step": 270
},
{
"epoch": 0.11,
"learning_rate": 0.0002,
"loss": 0.5487,
"step": 280
},
{
"epoch": 0.12,
"learning_rate": 0.0002,
"loss": 0.5345,
"step": 290
},
{
"epoch": 0.12,
"learning_rate": 0.0002,
"loss": 0.6299,
"step": 300
},
{
"epoch": 0.13,
"learning_rate": 0.0002,
"loss": 0.5681,
"step": 310
},
{
"epoch": 0.13,
"learning_rate": 0.0002,
"loss": 0.5553,
"step": 320
},
{
"epoch": 0.13,
"learning_rate": 0.0002,
"loss": 0.575,
"step": 330
},
{
"epoch": 0.14,
"learning_rate": 0.0002,
"loss": 0.5708,
"step": 340
},
{
"epoch": 0.14,
"learning_rate": 0.0002,
"loss": 0.4932,
"step": 350
},
{
"epoch": 0.15,
"learning_rate": 0.0002,
"loss": 0.6957,
"step": 360
},
{
"epoch": 0.15,
"learning_rate": 0.0002,
"loss": 0.6442,
"step": 370
},
{
"epoch": 0.15,
"learning_rate": 0.0002,
"loss": 0.5999,
"step": 380
},
{
"epoch": 0.16,
"learning_rate": 0.0002,
"loss": 0.5086,
"step": 390
},
{
"epoch": 0.16,
"learning_rate": 0.0002,
"loss": 0.7349,
"step": 400
},
{
"epoch": 0.16,
"eval_loss": 0.6260886192321777,
"eval_runtime": 94.1289,
"eval_samples_per_second": 10.624,
"eval_steps_per_second": 5.312,
"step": 400
},
{
"epoch": 0.16,
"mmlu_eval_accuracy": 0.4735216064792921,
"mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
"mmlu_eval_accuracy_anatomy": 0.5714285714285714,
"mmlu_eval_accuracy_astronomy": 0.5,
"mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
"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": 0.2727272727272727,
"mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
"mmlu_eval_accuracy_college_medicine": 0.4090909090909091,
"mmlu_eval_accuracy_college_physics": 0.45454545454545453,
"mmlu_eval_accuracy_computer_security": 0.5454545454545454,
"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": 0.34146341463414637,
"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": 0.4444444444444444,
"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": 0.6190476190476191,
"mmlu_eval_accuracy_high_school_macroeconomics": 0.4186046511627907,
"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": 0.75,
"mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
"mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
"mmlu_eval_accuracy_high_school_world_history": 0.5,
"mmlu_eval_accuracy_human_aging": 0.6956521739130435,
"mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
"mmlu_eval_accuracy_international_law": 0.8461538461538461,
"mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
"mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
"mmlu_eval_accuracy_machine_learning": 0.36363636363636365,
"mmlu_eval_accuracy_management": 0.45454545454545453,
"mmlu_eval_accuracy_marketing": 0.8,
"mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
"mmlu_eval_accuracy_miscellaneous": 0.6162790697674418,
"mmlu_eval_accuracy_moral_disputes": 0.5263157894736842,
"mmlu_eval_accuracy_moral_scenarios": 0.24,
"mmlu_eval_accuracy_nutrition": 0.6666666666666666,
"mmlu_eval_accuracy_philosophy": 0.47058823529411764,
"mmlu_eval_accuracy_prehistory": 0.5142857142857142,
"mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
"mmlu_eval_accuracy_professional_law": 0.3352941176470588,
"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": 0.4444444444444444,
"mmlu_eval_accuracy_sociology": 0.7272727272727273,
"mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
"mmlu_eval_accuracy_virology": 0.4444444444444444,
"mmlu_eval_accuracy_world_religions": 0.7368421052631579,
"mmlu_loss": 0.9645495347814834,
"step": 400
},
{
"epoch": 0.17,
"learning_rate": 0.0002,
"loss": 0.6117,
"step": 410
},
{
"epoch": 0.17,
"learning_rate": 0.0002,
"loss": 0.5963,
"step": 420
},
{
"epoch": 0.17,
"learning_rate": 0.0002,
"loss": 0.5866,
"step": 430
},
{
"epoch": 0.18,
"learning_rate": 0.0002,
"loss": 0.5433,
"step": 440
},
{
"epoch": 0.18,
"learning_rate": 0.0002,
"loss": 0.5432,
"step": 450
},
{
"epoch": 0.19,
"learning_rate": 0.0002,
"loss": 0.5713,
"step": 460
},
{
"epoch": 0.19,
"learning_rate": 0.0002,
"loss": 0.5957,
"step": 470
},
{
"epoch": 0.19,
"learning_rate": 0.0002,
"loss": 0.6526,
"step": 480
},
{
"epoch": 0.2,
"learning_rate": 0.0002,
"loss": 0.57,
"step": 490
},
{
"epoch": 0.2,
"learning_rate": 0.0002,
"loss": 0.5938,
"step": 500
},
{
"epoch": 0.21,
"learning_rate": 0.0002,
"loss": 0.6141,
"step": 510
},
{
"epoch": 0.21,
"learning_rate": 0.0002,
"loss": 0.5262,
"step": 520
},
{
"epoch": 0.21,
"learning_rate": 0.0002,
"loss": 0.7055,
"step": 530
},
{
"epoch": 0.22,
"learning_rate": 0.0002,
"loss": 0.5412,
"step": 540
},
{
"epoch": 0.22,
"learning_rate": 0.0002,
"loss": 0.4956,
"step": 550
},
{
"epoch": 0.23,
"learning_rate": 0.0002,
"loss": 0.6345,
"step": 560
},
{
"epoch": 0.23,
"learning_rate": 0.0002,
"loss": 0.5665,
"step": 570
},
{
"epoch": 0.23,
"learning_rate": 0.0002,
"loss": 0.6687,
"step": 580
},
{
"epoch": 0.24,
"learning_rate": 0.0002,
"loss": 0.5994,
"step": 590
},
{
"epoch": 0.24,
"learning_rate": 0.0002,
"loss": 0.6209,
"step": 600
},
{
"epoch": 0.24,
"eval_loss": 0.6194782853126526,
"eval_runtime": 94.0475,
"eval_samples_per_second": 10.633,
"eval_steps_per_second": 5.316,
"step": 600
},
{
"epoch": 0.24,
"mmlu_eval_accuracy": 0.44690777926110636,
"mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
"mmlu_eval_accuracy_anatomy": 0.42857142857142855,
"mmlu_eval_accuracy_astronomy": 0.375,
"mmlu_eval_accuracy_business_ethics": 0.6363636363636364,
"mmlu_eval_accuracy_clinical_knowledge": 0.41379310344827586,
"mmlu_eval_accuracy_college_biology": 0.375,
"mmlu_eval_accuracy_college_chemistry": 0.0,
"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": 0.5454545454545454,
"mmlu_eval_accuracy_computer_security": 0.36363636363636365,
"mmlu_eval_accuracy_conceptual_physics": 0.3076923076923077,
"mmlu_eval_accuracy_econometrics": 0.25,
"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": 0.2,
"mmlu_eval_accuracy_high_school_biology": 0.28125,
"mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091,
"mmlu_eval_accuracy_high_school_computer_science": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_geography": 0.6818181818181818,
"mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714,
"mmlu_eval_accuracy_high_school_macroeconomics": 0.3488372093023256,
"mmlu_eval_accuracy_high_school_mathematics": 0.3103448275862069,
"mmlu_eval_accuracy_high_school_microeconomics": 0.38461538461538464,
"mmlu_eval_accuracy_high_school_physics": 0.17647058823529413,
"mmlu_eval_accuracy_high_school_psychology": 0.6833333333333333,
"mmlu_eval_accuracy_high_school_statistics": 0.2608695652173913,
"mmlu_eval_accuracy_high_school_us_history": 0.7272727272727273,
"mmlu_eval_accuracy_high_school_world_history": 0.5384615384615384,
"mmlu_eval_accuracy_human_aging": 0.6521739130434783,
"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": 0.09090909090909091,
"mmlu_eval_accuracy_management": 0.36363636363636365,
"mmlu_eval_accuracy_marketing": 0.72,
"mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
"mmlu_eval_accuracy_miscellaneous": 0.6744186046511628,
"mmlu_eval_accuracy_moral_disputes": 0.42105263157894735,
"mmlu_eval_accuracy_moral_scenarios": 0.24,
"mmlu_eval_accuracy_nutrition": 0.5454545454545454,
"mmlu_eval_accuracy_philosophy": 0.5588235294117647,
"mmlu_eval_accuracy_prehistory": 0.42857142857142855,
"mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
"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": 0.5,
"mmlu_eval_accuracy_security_studies": 0.4444444444444444,
"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": 0.9532866988613151,
"step": 600
}
],
"max_steps": 5000,
"num_train_epochs": 3,
"total_flos": 5.07092062542889e+16,
"trial_name": null,
"trial_params": null
}