train_log.csv

iter,loss,L_he_ema,L_ihc_ema,frac_he_steps,wall_min
1,0.324302,0.000000,0.324302,0.000,0.12
100,0.043342,0.065942,0.081857,0.535,2.51
200,0.097045,0.054950,0.072664,0.580,5.02
300,0.026623,0.055695,0.043483,0.510,7.51
400,0.051844,0.051799,0.047156,0.400,10.03
500,0.047274,0.052398,0.053334,0.520,12.55
600,0.039756,0.045176,0.039605,0.530,15.27
700,0.040362,0.047732,0.035761,0.510,17.89
800,0.049542,0.056743,0.041526,0.480,20.55
900,0.030575,0.045782,0.032057,0.500,23.07
1000,0.042467,0.061811,0.046647,0.480,25.60
1100,0.034238,0.041705,0.038459,0.540,28.54
1200,0.018491,0.049659,0.042841,0.550,31.28
1300,0.021324,0.046538,0.038818,0.570,33.92
1400,0.049506,0.043883,0.039027,0.540,36.42
1500,0.034629,0.041203,0.039800,0.580,38.96
1600,0.027662,0.038047,0.027223,0.490,41.74
1700,0.040613,0.049979,0.026589,0.460,44.25
1800,0.017908,0.042587,0.031309,0.550,46.67
1900,0.027759,0.039529,0.030349,0.490,49.21
2000,0.012190,0.033719,0.022770,0.560,51.82
2100,0.036526,0.045941,0.034931,0.530,54.65
2200,0.019214,0.040566,0.027344,0.520,57.16
2300,0.039643,0.038911,0.028586,0.440,59.71
2400,0.023114,0.035536,0.025342,0.480,62.27
2500,0.044968,0.038114,0.025877,0.540,64.81
2600,0.037182,0.044849,0.028349,0.450,67.56
2700,0.035828,0.036466,0.029197,0.510,70.08
2800,0.049414,0.045787,0.030251,0.640,72.69
2900,0.021199,0.032433,0.024000,0.480,75.21
3000,0.033280,0.038864,0.027389,0.460,77.80