prateeky2806's picture
Training in progress, step 400
26c4add
raw
history blame
12.6 kB
{
"best_metric": 0.5613595843315125,
"best_model_checkpoint": "./output_v2/7b_cluster016_Nous-Hermes-llama-2-7b_partitioned_v3_standardized_016/checkpoint-400",
"epoch": 0.6683375104427736,
"global_step": 400,
"is_hyper_param_search": false,
"is_local_process_zero": true,
"is_world_process_zero": true,
"log_history": [
{
"epoch": 0.02,
"learning_rate": 0.0002,
"loss": 0.6709,
"step": 10
},
{
"epoch": 0.03,
"learning_rate": 0.0002,
"loss": 0.6086,
"step": 20
},
{
"epoch": 0.05,
"learning_rate": 0.0002,
"loss": 0.6457,
"step": 30
},
{
"epoch": 0.07,
"learning_rate": 0.0002,
"loss": 0.5722,
"step": 40
},
{
"epoch": 0.08,
"learning_rate": 0.0002,
"loss": 0.6039,
"step": 50
},
{
"epoch": 0.1,
"learning_rate": 0.0002,
"loss": 0.6079,
"step": 60
},
{
"epoch": 0.12,
"learning_rate": 0.0002,
"loss": 0.6261,
"step": 70
},
{
"epoch": 0.13,
"learning_rate": 0.0002,
"loss": 0.5876,
"step": 80
},
{
"epoch": 0.15,
"learning_rate": 0.0002,
"loss": 0.5645,
"step": 90
},
{
"epoch": 0.17,
"learning_rate": 0.0002,
"loss": 0.5902,
"step": 100
},
{
"epoch": 0.18,
"learning_rate": 0.0002,
"loss": 0.6008,
"step": 110
},
{
"epoch": 0.2,
"learning_rate": 0.0002,
"loss": 0.588,
"step": 120
},
{
"epoch": 0.22,
"learning_rate": 0.0002,
"loss": 0.6001,
"step": 130
},
{
"epoch": 0.23,
"learning_rate": 0.0002,
"loss": 0.5684,
"step": 140
},
{
"epoch": 0.25,
"learning_rate": 0.0002,
"loss": 0.5776,
"step": 150
},
{
"epoch": 0.27,
"learning_rate": 0.0002,
"loss": 0.5482,
"step": 160
},
{
"epoch": 0.28,
"learning_rate": 0.0002,
"loss": 0.5759,
"step": 170
},
{
"epoch": 0.3,
"learning_rate": 0.0002,
"loss": 0.5736,
"step": 180
},
{
"epoch": 0.32,
"learning_rate": 0.0002,
"loss": 0.5417,
"step": 190
},
{
"epoch": 0.33,
"learning_rate": 0.0002,
"loss": 0.5581,
"step": 200
},
{
"epoch": 0.33,
"eval_loss": 0.5835912227630615,
"eval_runtime": 210.8375,
"eval_samples_per_second": 4.743,
"eval_steps_per_second": 2.371,
"step": 200
},
{
"epoch": 0.33,
"mmlu_eval_accuracy": 0.46615455952712886,
"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": 0.41379310344827586,
"mmlu_eval_accuracy_college_biology": 0.5,
"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": 0.2727272727272727,
"mmlu_eval_accuracy_conceptual_physics": 0.34615384615384615,
"mmlu_eval_accuracy_econometrics": 0.16666666666666666,
"mmlu_eval_accuracy_electrical_engineering": 0.4375,
"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": 0.7777777777777778,
"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": 0.2413793103448276,
"mmlu_eval_accuracy_high_school_microeconomics": 0.4230769230769231,
"mmlu_eval_accuracy_high_school_physics": 0.35294117647058826,
"mmlu_eval_accuracy_high_school_psychology": 0.7,
"mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
"mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
"mmlu_eval_accuracy_high_school_world_history": 0.5,
"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": 0.36363636363636365,
"mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
"mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
"mmlu_eval_accuracy_management": 0.45454545454545453,
"mmlu_eval_accuracy_marketing": 0.76,
"mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
"mmlu_eval_accuracy_miscellaneous": 0.686046511627907,
"mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
"mmlu_eval_accuracy_moral_scenarios": 0.23,
"mmlu_eval_accuracy_nutrition": 0.6060606060606061,
"mmlu_eval_accuracy_philosophy": 0.4411764705882353,
"mmlu_eval_accuracy_prehistory": 0.4857142857142857,
"mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
"mmlu_eval_accuracy_professional_law": 0.3352941176470588,
"mmlu_eval_accuracy_professional_medicine": 0.3870967741935484,
"mmlu_eval_accuracy_professional_psychology": 0.36231884057971014,
"mmlu_eval_accuracy_public_relations": 0.5833333333333334,
"mmlu_eval_accuracy_security_studies": 0.5925925925925926,
"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": 1.1704803334048148,
"step": 200
},
{
"epoch": 0.35,
"learning_rate": 0.0002,
"loss": 0.5413,
"step": 210
},
{
"epoch": 0.37,
"learning_rate": 0.0002,
"loss": 0.5632,
"step": 220
},
{
"epoch": 0.38,
"learning_rate": 0.0002,
"loss": 0.5752,
"step": 230
},
{
"epoch": 0.4,
"learning_rate": 0.0002,
"loss": 0.5583,
"step": 240
},
{
"epoch": 0.42,
"learning_rate": 0.0002,
"loss": 0.5274,
"step": 250
},
{
"epoch": 0.43,
"learning_rate": 0.0002,
"loss": 0.6163,
"step": 260
},
{
"epoch": 0.45,
"learning_rate": 0.0002,
"loss": 0.5673,
"step": 270
},
{
"epoch": 0.47,
"learning_rate": 0.0002,
"loss": 0.5241,
"step": 280
},
{
"epoch": 0.48,
"learning_rate": 0.0002,
"loss": 0.5564,
"step": 290
},
{
"epoch": 0.5,
"learning_rate": 0.0002,
"loss": 0.5451,
"step": 300
},
{
"epoch": 0.52,
"learning_rate": 0.0002,
"loss": 0.5661,
"step": 310
},
{
"epoch": 0.53,
"learning_rate": 0.0002,
"loss": 0.5467,
"step": 320
},
{
"epoch": 0.55,
"learning_rate": 0.0002,
"loss": 0.5513,
"step": 330
},
{
"epoch": 0.57,
"learning_rate": 0.0002,
"loss": 0.5999,
"step": 340
},
{
"epoch": 0.58,
"learning_rate": 0.0002,
"loss": 0.5518,
"step": 350
},
{
"epoch": 0.6,
"learning_rate": 0.0002,
"loss": 0.4896,
"step": 360
},
{
"epoch": 0.62,
"learning_rate": 0.0002,
"loss": 0.5314,
"step": 370
},
{
"epoch": 0.63,
"learning_rate": 0.0002,
"loss": 0.5495,
"step": 380
},
{
"epoch": 0.65,
"learning_rate": 0.0002,
"loss": 0.553,
"step": 390
},
{
"epoch": 0.67,
"learning_rate": 0.0002,
"loss": 0.5324,
"step": 400
},
{
"epoch": 0.67,
"eval_loss": 0.5613595843315125,
"eval_runtime": 210.7546,
"eval_samples_per_second": 4.745,
"eval_steps_per_second": 2.372,
"step": 400
},
{
"epoch": 0.67,
"mmlu_eval_accuracy": 0.47295524277138523,
"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": 0.375,
"mmlu_eval_accuracy_college_chemistry": 0.125,
"mmlu_eval_accuracy_college_computer_science": 0.45454545454545453,
"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": 0.36363636363636365,
"mmlu_eval_accuracy_conceptual_physics": 0.34615384615384615,
"mmlu_eval_accuracy_econometrics": 0.16666666666666666,
"mmlu_eval_accuracy_electrical_engineering": 0.4375,
"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": 0.36363636363636365,
"mmlu_eval_accuracy_high_school_computer_science": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
"mmlu_eval_accuracy_high_school_geography": 0.8181818181818182,
"mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
"mmlu_eval_accuracy_high_school_macroeconomics": 0.3488372093023256,
"mmlu_eval_accuracy_high_school_mathematics": 0.3448275862068966,
"mmlu_eval_accuracy_high_school_microeconomics": 0.38461538461538464,
"mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
"mmlu_eval_accuracy_high_school_psychology": 0.7166666666666667,
"mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
"mmlu_eval_accuracy_high_school_us_history": 0.7272727272727273,
"mmlu_eval_accuracy_high_school_world_history": 0.5,
"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": 0.36363636363636365,
"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": 0.6744186046511628,
"mmlu_eval_accuracy_moral_disputes": 0.42105263157894735,
"mmlu_eval_accuracy_moral_scenarios": 0.23,
"mmlu_eval_accuracy_nutrition": 0.6060606060606061,
"mmlu_eval_accuracy_philosophy": 0.47058823529411764,
"mmlu_eval_accuracy_prehistory": 0.4857142857142857,
"mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
"mmlu_eval_accuracy_professional_law": 0.35294117647058826,
"mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
"mmlu_eval_accuracy_professional_psychology": 0.37681159420289856,
"mmlu_eval_accuracy_public_relations": 0.5,
"mmlu_eval_accuracy_security_studies": 0.48148148148148145,
"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": 1.1208655159366037,
"step": 400
}
],
"max_steps": 5000,
"num_train_epochs": 9,
"total_flos": 9.749315379481805e+16,
"trial_name": null,
"trial_params": null
}