prateeky2806's picture
Training in progress, step 600
f032b81
raw
history blame
18.7 kB
{
"best_metric": 0.4673095643520355,
"best_model_checkpoint": "./output_v2/7b_cluster017_Nous-Hermes-llama-2-7b_partitioned_v3_standardized_017/checkpoint-600",
"epoch": 0.7168458781362007,
"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": 0.5801,
"step": 10
},
{
"epoch": 0.02,
"learning_rate": 0.0002,
"loss": 0.6179,
"step": 20
},
{
"epoch": 0.04,
"learning_rate": 0.0002,
"loss": 0.5163,
"step": 30
},
{
"epoch": 0.05,
"learning_rate": 0.0002,
"loss": 0.5249,
"step": 40
},
{
"epoch": 0.06,
"learning_rate": 0.0002,
"loss": 0.5421,
"step": 50
},
{
"epoch": 0.07,
"learning_rate": 0.0002,
"loss": 0.4993,
"step": 60
},
{
"epoch": 0.08,
"learning_rate": 0.0002,
"loss": 0.5421,
"step": 70
},
{
"epoch": 0.1,
"learning_rate": 0.0002,
"loss": 0.4769,
"step": 80
},
{
"epoch": 0.11,
"learning_rate": 0.0002,
"loss": 0.5084,
"step": 90
},
{
"epoch": 0.12,
"learning_rate": 0.0002,
"loss": 0.4731,
"step": 100
},
{
"epoch": 0.13,
"learning_rate": 0.0002,
"loss": 0.5069,
"step": 110
},
{
"epoch": 0.14,
"learning_rate": 0.0002,
"loss": 0.4659,
"step": 120
},
{
"epoch": 0.16,
"learning_rate": 0.0002,
"loss": 0.4863,
"step": 130
},
{
"epoch": 0.17,
"learning_rate": 0.0002,
"loss": 0.5124,
"step": 140
},
{
"epoch": 0.18,
"learning_rate": 0.0002,
"loss": 0.5311,
"step": 150
},
{
"epoch": 0.19,
"learning_rate": 0.0002,
"loss": 0.5032,
"step": 160
},
{
"epoch": 0.2,
"learning_rate": 0.0002,
"loss": 0.5065,
"step": 170
},
{
"epoch": 0.22,
"learning_rate": 0.0002,
"loss": 0.4613,
"step": 180
},
{
"epoch": 0.23,
"learning_rate": 0.0002,
"loss": 0.517,
"step": 190
},
{
"epoch": 0.24,
"learning_rate": 0.0002,
"loss": 0.4761,
"step": 200
},
{
"epoch": 0.24,
"eval_loss": 0.4977516829967499,
"eval_runtime": 178.665,
"eval_samples_per_second": 5.597,
"eval_steps_per_second": 2.799,
"step": 200
},
{
"epoch": 0.24,
"mmlu_eval_accuracy": 0.4731690276039549,
"mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
"mmlu_eval_accuracy_anatomy": 0.6428571428571429,
"mmlu_eval_accuracy_astronomy": 0.4375,
"mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
"mmlu_eval_accuracy_clinical_knowledge": 0.41379310344827586,
"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": 0.4090909090909091,
"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": 0.5625,
"mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
"mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
"mmlu_eval_accuracy_global_facts": 0.6,
"mmlu_eval_accuracy_high_school_biology": 0.34375,
"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": 0.6666666666666666,
"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": 0.35294117647058826,
"mmlu_eval_accuracy_high_school_psychology": 0.7333333333333333,
"mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
"mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
"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": 0.6923076923076923,
"mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
"mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
"mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
"mmlu_eval_accuracy_management": 0.6363636363636364,
"mmlu_eval_accuracy_marketing": 0.68,
"mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
"mmlu_eval_accuracy_miscellaneous": 0.6511627906976745,
"mmlu_eval_accuracy_moral_disputes": 0.42105263157894735,
"mmlu_eval_accuracy_moral_scenarios": 0.23,
"mmlu_eval_accuracy_nutrition": 0.6363636363636364,
"mmlu_eval_accuracy_philosophy": 0.47058823529411764,
"mmlu_eval_accuracy_prehistory": 0.5142857142857142,
"mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
"mmlu_eval_accuracy_professional_law": 0.32941176470588235,
"mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
"mmlu_eval_accuracy_professional_psychology": 0.34782608695652173,
"mmlu_eval_accuracy_public_relations": 0.5833333333333334,
"mmlu_eval_accuracy_security_studies": 0.48148148148148145,
"mmlu_eval_accuracy_sociology": 0.6363636363636364,
"mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
"mmlu_eval_accuracy_virology": 0.4444444444444444,
"mmlu_eval_accuracy_world_religions": 0.7368421052631579,
"mmlu_loss": 1.201889930774431,
"step": 200
},
{
"epoch": 0.25,
"learning_rate": 0.0002,
"loss": 0.447,
"step": 210
},
{
"epoch": 0.26,
"learning_rate": 0.0002,
"loss": 0.5419,
"step": 220
},
{
"epoch": 0.27,
"learning_rate": 0.0002,
"loss": 0.46,
"step": 230
},
{
"epoch": 0.29,
"learning_rate": 0.0002,
"loss": 0.481,
"step": 240
},
{
"epoch": 0.3,
"learning_rate": 0.0002,
"loss": 0.4279,
"step": 250
},
{
"epoch": 0.31,
"learning_rate": 0.0002,
"loss": 0.462,
"step": 260
},
{
"epoch": 0.32,
"learning_rate": 0.0002,
"loss": 0.4866,
"step": 270
},
{
"epoch": 0.33,
"learning_rate": 0.0002,
"loss": 0.4565,
"step": 280
},
{
"epoch": 0.35,
"learning_rate": 0.0002,
"loss": 0.4579,
"step": 290
},
{
"epoch": 0.36,
"learning_rate": 0.0002,
"loss": 0.4585,
"step": 300
},
{
"epoch": 0.37,
"learning_rate": 0.0002,
"loss": 0.466,
"step": 310
},
{
"epoch": 0.38,
"learning_rate": 0.0002,
"loss": 0.4766,
"step": 320
},
{
"epoch": 0.39,
"learning_rate": 0.0002,
"loss": 0.4682,
"step": 330
},
{
"epoch": 0.41,
"learning_rate": 0.0002,
"loss": 0.4467,
"step": 340
},
{
"epoch": 0.42,
"learning_rate": 0.0002,
"loss": 0.4675,
"step": 350
},
{
"epoch": 0.43,
"learning_rate": 0.0002,
"loss": 0.4816,
"step": 360
},
{
"epoch": 0.44,
"learning_rate": 0.0002,
"loss": 0.4439,
"step": 370
},
{
"epoch": 0.45,
"learning_rate": 0.0002,
"loss": 0.4553,
"step": 380
},
{
"epoch": 0.47,
"learning_rate": 0.0002,
"loss": 0.4707,
"step": 390
},
{
"epoch": 0.48,
"learning_rate": 0.0002,
"loss": 0.4389,
"step": 400
},
{
"epoch": 0.48,
"eval_loss": 0.4804040491580963,
"eval_runtime": 178.9419,
"eval_samples_per_second": 5.588,
"eval_steps_per_second": 2.794,
"step": 400
},
{
"epoch": 0.48,
"mmlu_eval_accuracy": 0.4686810757119835,
"mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
"mmlu_eval_accuracy_anatomy": 0.5,
"mmlu_eval_accuracy_astronomy": 0.4375,
"mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
"mmlu_eval_accuracy_clinical_knowledge": 0.41379310344827586,
"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": 0.36363636363636365,
"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": 0.375,
"mmlu_eval_accuracy_elementary_mathematics": 0.36585365853658536,
"mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
"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": 0.6111111111111112,
"mmlu_eval_accuracy_high_school_geography": 0.8636363636363636,
"mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_macroeconomics": 0.3023255813953488,
"mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
"mmlu_eval_accuracy_high_school_microeconomics": 0.38461538461538464,
"mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
"mmlu_eval_accuracy_high_school_psychology": 0.7666666666666667,
"mmlu_eval_accuracy_high_school_statistics": 0.43478260869565216,
"mmlu_eval_accuracy_high_school_us_history": 0.6818181818181818,
"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": 0.6923076923076923,
"mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
"mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
"mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
"mmlu_eval_accuracy_management": 0.5454545454545454,
"mmlu_eval_accuracy_marketing": 0.76,
"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": 0.6060606060606061,
"mmlu_eval_accuracy_philosophy": 0.47058823529411764,
"mmlu_eval_accuracy_prehistory": 0.5142857142857142,
"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": 0.37681159420289856,
"mmlu_eval_accuracy_public_relations": 0.5833333333333334,
"mmlu_eval_accuracy_security_studies": 0.5185185185185185,
"mmlu_eval_accuracy_sociology": 0.6363636363636364,
"mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
"mmlu_eval_accuracy_virology": 0.4444444444444444,
"mmlu_eval_accuracy_world_religions": 0.7368421052631579,
"mmlu_loss": 1.168120609523422,
"step": 400
},
{
"epoch": 0.49,
"learning_rate": 0.0002,
"loss": 0.49,
"step": 410
},
{
"epoch": 0.5,
"learning_rate": 0.0002,
"loss": 0.4614,
"step": 420
},
{
"epoch": 0.51,
"learning_rate": 0.0002,
"loss": 0.4711,
"step": 430
},
{
"epoch": 0.53,
"learning_rate": 0.0002,
"loss": 0.4557,
"step": 440
},
{
"epoch": 0.54,
"learning_rate": 0.0002,
"loss": 0.4454,
"step": 450
},
{
"epoch": 0.55,
"learning_rate": 0.0002,
"loss": 0.4819,
"step": 460
},
{
"epoch": 0.56,
"learning_rate": 0.0002,
"loss": 0.4694,
"step": 470
},
{
"epoch": 0.57,
"learning_rate": 0.0002,
"loss": 0.4602,
"step": 480
},
{
"epoch": 0.59,
"learning_rate": 0.0002,
"loss": 0.4528,
"step": 490
},
{
"epoch": 0.6,
"learning_rate": 0.0002,
"loss": 0.4415,
"step": 500
},
{
"epoch": 0.61,
"learning_rate": 0.0002,
"loss": 0.4597,
"step": 510
},
{
"epoch": 0.62,
"learning_rate": 0.0002,
"loss": 0.437,
"step": 520
},
{
"epoch": 0.63,
"learning_rate": 0.0002,
"loss": 0.4649,
"step": 530
},
{
"epoch": 0.65,
"learning_rate": 0.0002,
"loss": 0.4552,
"step": 540
},
{
"epoch": 0.66,
"learning_rate": 0.0002,
"loss": 0.4517,
"step": 550
},
{
"epoch": 0.67,
"learning_rate": 0.0002,
"loss": 0.4324,
"step": 560
},
{
"epoch": 0.68,
"learning_rate": 0.0002,
"loss": 0.4473,
"step": 570
},
{
"epoch": 0.69,
"learning_rate": 0.0002,
"loss": 0.4611,
"step": 580
},
{
"epoch": 0.7,
"learning_rate": 0.0002,
"loss": 0.4378,
"step": 590
},
{
"epoch": 0.72,
"learning_rate": 0.0002,
"loss": 0.4337,
"step": 600
},
{
"epoch": 0.72,
"eval_loss": 0.4673095643520355,
"eval_runtime": 178.8409,
"eval_samples_per_second": 5.592,
"eval_steps_per_second": 2.796,
"step": 600
},
{
"epoch": 0.72,
"mmlu_eval_accuracy": 0.4657957744296099,
"mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
"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": 0.4375,
"mmlu_eval_accuracy_college_chemistry": 0.125,
"mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
"mmlu_eval_accuracy_college_mathematics": 0.36363636363636365,
"mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
"mmlu_eval_accuracy_college_physics": 0.45454545454545453,
"mmlu_eval_accuracy_computer_security": 0.45454545454545453,
"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": 0.3170731707317073,
"mmlu_eval_accuracy_formal_logic": 0.21428571428571427,
"mmlu_eval_accuracy_global_facts": 0.5,
"mmlu_eval_accuracy_high_school_biology": 0.40625,
"mmlu_eval_accuracy_high_school_chemistry": 0.36363636363636365,
"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": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_macroeconomics": 0.37209302325581395,
"mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
"mmlu_eval_accuracy_high_school_microeconomics": 0.5,
"mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
"mmlu_eval_accuracy_high_school_psychology": 0.75,
"mmlu_eval_accuracy_high_school_statistics": 0.4782608695652174,
"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": 0.6923076923076923,
"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": 0.68,
"mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
"mmlu_eval_accuracy_miscellaneous": 0.627906976744186,
"mmlu_eval_accuracy_moral_disputes": 0.5,
"mmlu_eval_accuracy_moral_scenarios": 0.23,
"mmlu_eval_accuracy_nutrition": 0.6363636363636364,
"mmlu_eval_accuracy_philosophy": 0.4411764705882353,
"mmlu_eval_accuracy_prehistory": 0.5428571428571428,
"mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
"mmlu_eval_accuracy_professional_law": 0.3176470588235294,
"mmlu_eval_accuracy_professional_medicine": 0.45161290322580644,
"mmlu_eval_accuracy_professional_psychology": 0.34782608695652173,
"mmlu_eval_accuracy_public_relations": 0.5,
"mmlu_eval_accuracy_security_studies": 0.48148148148148145,
"mmlu_eval_accuracy_sociology": 0.5909090909090909,
"mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
"mmlu_eval_accuracy_virology": 0.3888888888888889,
"mmlu_eval_accuracy_world_religions": 0.7368421052631579,
"mmlu_loss": 1.1695979737893096,
"step": 600
}
],
"max_steps": 5000,
"num_train_epochs": 6,
"total_flos": 1.2298556702785536e+17,
"trial_name": null,
"trial_params": null
}